CDT Management

Dr Adam Hampshire is a Senior Lecturer at the Computational, Cognitive and Clinical Neuroimaging Laboratory, which is part of the Imperial College London Department of Medicine’s Division of Brain Sciences. His research focuses on deriving a better understanding of how large-scale networks in the human brain coordinate in order to support key aspects of cognition such as attention, motor response inhibition, working memory, planning and reasoning. He also investigates how these aspects of brain function are affected in neurological and psychiatric populations, and how they relate to variability in intelligence within the general population. His group are currently applying an interdisciplinary combination of techniques in pursuit of this aim including functional and structural brain imaging, electroencephalography, neurostimulation, machine learning, computational modelling, and large scale remote behavioural testing via Apps and websites.

a.hampshire@imperial.ac.uk

Dr Adelaide de Vecchi is a Lecturer in Computational Cardiovascular Modelling in the Department of Biomedical Engineering within the School of Biomedical Engineering & Imaging Sciences at King’s College London. The focus of her research is on the field of personalised medicine, specifically on the clinical translation of computational modelling applied to cardiovascular diseases. She has developed personalised models of fluid-structure interaction based on state-of-the-art imaging data, including CT, Phase-Contrast MRI (4d flow) and 3D+t Colour Doppler data. These models have been used to gain insight into the pathophysiology of congenital heart diseases (e.g. single ventricle pathologies) and to evaluate medical devices (e.g. bioprosthetic mitral valves) in the individual patient. Her research has a strong emphasis on multi-disciplinarity and clinical translation, and she works in close collaboration with cardiologists, surgeons, imaging scientists and software developers.

adelaide.de_vecchi@kcl.ac.uk

Alan Spivey is Professor of Synthetic Chemistry in the Department of Chemistry at Imperial College London. His research encompasses the development of new catalysts for asymmetric group transfer reactions (acylation, sulfonyation & phosphorylation), germanium chemistry, chemical aspects of signal transduction, total synthesis and medicinal/imaging chemistry relating to asthma and cancer targets. In particular, his group has interests in the use of 18F and 68Ga-based positron emission tomography (PET) for imaging via pre-targetting of various cancers. The work is funded by EPSRC, BBSRC, The Wellcome Trust, The Leverhulme Trust, CRUK, Pfizer, GlazoSmithKline, AstraZeneca, Syngenta, Avecia, Sanofi-Synthelabo, Roche, and Amersham Health. Read more about his research.

For further details of his groups’ research activities see: www.imperial.ac.uk/spiveygroup

a.c.spivey@imperial.ac.uk

Professor Aldo Rinaldi is a Consultant Cardiologist at Guy’s & St Thomas’ NHS Foundation Trust. He trained in Medicine at King’s College Hospital becoming a member of the Royal College of Physicians in 1993 and subsequently a Fellow in 2006. He undertook his training in Cardiology at Guy’s & St Thomas’ Hospitals with dual accreditation in Cardiology & General Medicine. He undertook his Research at the University Hospital of Wales and the Hammersmith Hospital gaining his MD in 2001. He became a Fellow of the Heart Rhythm Society in 2013. In 2014 he was promoted to Professor of Cardiac Electrophysiology and Devices at King’s Dollege London. He practices as an Interventional Cardiologist/Electrophysiologist specializing in the treatment of cardiac arrhythmias and heart failure, electrophysiology/radiofrequency ablation and complex pacing. He has a special interest in Cardiac Resynchronisation Therapy for heart failure, laser lead extraction and treatment of atrial fibrillation. He leads the Cardiac Device service at St Thomas’ Hospital and the Cardiac Device Research Programme. He has published over 300 peer reviewed papers and book chapters.

Alexander Hammers is Professor of Imaging and Neuroscience and Head of the King’s College London & Guy’s and St Thomas’ PET Centre at St Thomas’ Hospital. A neurologist with a particular interest in epilepsy, he has substantial methodological expertise in quantitative ligand PET and quantitative structural MRI (atlasing). His research interests include the use of imaging to elucidate the neurobiology of epilepsy, work towards the noninvasive determination of epileptogenic areas during the presurgical workup, determine normal and abnormal patterns of brain changes over time, including in the neurodegenerative diseases (e.g. Alzheimer’s disease) and automatically classify medical images. He has interests in imaging methodology, including the development of simultaneous MRI-PET.

alexander.hammers@kcl.ac.uk

Alistair Young is Professor of Cardiovascular Data Analytics and Artificial Intelligence in the Biomedical Engineering Department within the King’s School of Biomedical Engineering & Imaging Sciences. His research interests are in imaging, biomedical engineering and statistical modelling of cardiovascular disease. He has been funded by the National Institutes of Health (USA), the Wellcome Trust (UK), and the Health Research Council of New Zealand. He has extensive experience working with industry to translate technologies into clinical products. He has published widely in high impact journals with over 130 journal publications.

One key area of focus is cardiac imaging in relation to heart failure, congenital heart disease, and biomechanics, with a focus on large scale statistical modelling of cohorts. This involves machine learning methods for automatic detection of heart structure and function, automatic identification of regional and global heart muscle disease, quantification of phenotypes and analysis of mechanisms for functional impairment.

alistair.young@kcl.ac.uk

Dr Alkystis Phinikaridou is a Senior Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Dr Phinikaridou received her PhD from Boston University in 2009. She joined the Biomedical Engineering Department at King’s in 2010 as Postdoctoral Research Associate and became Lecturer in Imaging Biology in 2016. Dr Phinikaridou’s research focuses on Molecular Imaging of Cardiovascular Diseases including atherosclerosis, aortic aneurysms, thrombosis, and myocardial infarction using MRI and PET/MRI in preclinical animal models. Her main areas of research include endothelial dysfunction, extracellular matrix turnover, and thrombosis. She also works towards translating the findings from the preclinical studies into the clinical field and bridging the gap between basic research and clinical applications.

Dr Phinikaridou and her group use experimental models to identify new biological targets for molecular imaging, design new contrast agents, and test the merits of both clinically approved and newly developed contrast agents to investigate the biological processes underlying different cardiovascular diseases. The main imaging biomarkers are endothelial permeability and dysfunction, extracellular matrix remodeling, including elastin, tropoelastin and collagen, and the organisation and resolution of thrombus. In addition to the preclinical work, the group also works on understanding the uptake mechanisms of clinically approved contrast agents and translating the preclinical findings into the clinical arena. Recently, the group initiated the first in-man study that focuses on the MRI characterization of thrombus in patients with deep vein thrombosis and how it relates to the outcome of endovascular treatment.

alkystis.1.phinikaridou@kcl.ac.uk

Professor Amedeo Chiribiri is Professor in Cardiovascular Imaging at King’s. In April 2013, Professor Chiribiri took up the post as Senior Lecturer in Cardiovascular Imaging at King’s College London and Honorary Consultant Cardiologist at Guy’s and St Thomas’ NHS Trust Foundation.
Since August 2013, Professor Chiribiri is the clinical lead for the non-congenital cardiac magnetic resonance service at Guy’s and St Thomas’ NHS Trust Foundation. The major aim of his current research is the investigation of novel cardiac MR techniques for the non-invasive assessment of cardiac structure and function. In particular, Professor Chiribiri’s research focuses on quantification of myocardial blood flow (perfusion) and on the development of novel methods for ischaemia detection and differential diagnosis based on advanced coronary physiology modelling, with a strong emphasis on rapid translation of new methodology into the clinic practice to evaluate benefit for the patient.
Moreover, Professor Chiribiri is actively involved in the development and validation of novel experimental models to simulate physiological and pathophysiological processes.

amedeo.chiribiri@kcl.ac.uk

Dr Anand Devaraj is an honorary senior lecturer at the National Heart and Lung Institute, which is part of the Imperial College London Faculty of Medicine, and consultant thoracic radiologist at the Royal Brompton Hospital. He is training programme director for radiology at the Royal Brompton.

Dr Devaraj’s areas of research interest and expertise are in CT of interstitial lung disease, lung cancer, lung nodules, and lung cancer screening.

He is President of the British Society of Thoracic Imaging, and Chair of the European Society of Thoracic Imaging Scientific Programme Committee.

Dr Andrew Melbourne is a senior lecturer in the Cardiovascular Imaging Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research team specialises in the design of computational imaging techniques to answer research questions in the growing fetus and neonate. His team are implementing imaging studies for supporting novel fetal interventions; for measuring the function of the placenta in utero; and for helping understand the links between extremely preterm birth and subsequent neuro-developmental outcome.

andrew.melbourne@kcl.ac.uk

Andrew Reader is Professor of Imaging Sciences in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His primary research interest concerns image reconstruction and modelling for positron emission tomography (PET), and more recently its integration with simultaneous magnetic resonance imaging (MRI). Particular topics include multi-parametric simultaneous PET-MR imaging, high resolution PET imaging of the brain, kinetic analysis, fully 4D image reconstruction and direct kinetic parameter estimation. He is passionate about learning of existing methodologies and then seeking to innovate, in order to demonstrate new possibilities without being prematurely concerned about the computational burden of novel approaches. Bayesian methods for estimation of end point parameters of interest directly from raw medical imaging data, along with improved modelling of the signal and noise components in the data, allow notable noise reduction and improved spatial resolution to be achieved in medical imaging.

Recent research output highlights include simultaneous water and glucose metabolism imaging with PET, creation of multi-subject radiotracer-specific brain atlases for use in automated analysis and as priors in image reconstruction, and direct kinetic parameter estimation for raclopride imaging of the dopaminergic system. Read more about Andrew’s research.

andrew.reader@kcl.ac.uk

Andrew Scott is a Senior Physicist at the Cardiovascular Magnetic Resonance Unit at the Royal Brompton Hospital and Honorary Senior Research Fellow at Imperial College London. His research is focussed on cardiac MRI and the microscopic structure and function of the heart. One key research area is in the development of diffusion tensor imaging methods, more typically used in neuroimaging, for use understanding the microstructure of the beating heart.

a.scott07@imperial.ac.uk

Andy King is a Reader in Medical Image Analysis in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses on the use of machine learning and deep learning in medical imaging. Much of Dr King’s work has focused on the analysis of dynamic imaging data that show the motion of organs, for example due to breathing or the beating of the heart. Cardiac image analysis (MRI and ultrasound) are specific areas of interest but the group have projects in a wide range of imaging applications. See more about Andy’s research on his group’s website.

andrew.king@kcl.ac.uk

Dr. Pouliopoulos received his B.Sc. in Physics from Aristotle University of Thessaloniki in 2011, with a specialization in solid state physics. As an undergraduate student, he conducted research in thin film characterization using X-ray absorption spectroscopy in the University of Bologna, Italy, and the European Synchrotron Radiation facility in Grenoble, France. He earned his M.Sc. in Nanotechnology and Regenerative Medicine from University College London, United Kingdom, in 2013, where he conducted research on positron emission mammography and magnetic resonance imaging using superparamagnetic iron oxide nanoparticles as contrast agents. He obtained his Ph.D. in Bioengineering from Imperial College London, United Kingdom, in 2017, for his work on controlling microbubble dynamics in ultrasound therapy. During his Ph.D., he developed multiple techniques in the field of therapeutic ultrasound, including rapid short-pulse therapy, Doppler passive acoustic mapping, and optical methods for investigating microbubble motion during ultrasound exposure. He worked as a postdoctoral research scientist and an associate research scientist in the Ultrasound Elasticity Imaging Laboratory at Columbia University, in New York City, NY, USA, from 2017 to 2021.

Starting November 2021, he is a lecturer in therapeutic ultrasound in the Department of Surgical and Interventional Engineering at King’s College London. He has received multiple awards and serves as a reviewer for 25 international peer-reviewed journals. He has mentored over 80 high-school, undergraduate and graduate students in their research projects and has been involved in outreach events promoting scientific research to the community. His research interests include targeted drug delivery using ultrasound, microbubble dynamics in ultrasound therapy, ultrasound therapy monitoring, and clinical translation of therapeutic ultrasound.

www.quiinlab.com

Ben Glocker is Reader in Machine Learning for Imaging at the Department of Computing at Imperial College London where he co-leads the Biomedical Image Analysis Group. He also leads the HeartFlow-Imperial Research Team. His research is at the intersection of medical imaging and artificial intelligence aiming to build computational tools for improving image-based detection and diagnosis of disease. Read more about Ben’s research.

b.glocker@imperial.ac.uk

Dr Bernhard Kainz is a Senior Lecturer in the Department of Computing at Imperial College London. He heads the human-in-the-loop computing group and is one of four academics leading the Biomedical Image Analysis, BioMedIA Collaboratory. Human-in-the-loop computing research aims at complementing human intelligence with machine capabilities and machine intelligence with human flexibility.

He co-creates intensively with the School of Biomedical Engineering & Imaging Sciences at King’s College London and the Department of Bioengineering at Imperial. He is Associate Editor for IEEE Transactions on Medical Imaging and a scientific adviser for ThinkSono Ltd and Ultromics Ltd. He is also Affordable Imaging stream lead for the EPSRC Centre for Doctoral Training in Smart Medical Imaging and involved in the UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare.

His research is about intelligent algorithms in healthcare, especially medical imaging. He is working on self-driving medical image acquisition that can guide human operators in real-time during diagnostics. Artificial Intelligence is currently used as a blanket term to describe research in these areas.

b.kainz@imperial.ac.uk

Dr Bram Ruijsink is a clinical fellow in cardiac imaging at the School of Imaging Sciences and Biomedical Engineering at King’s College London, with a focus on artificial intelligence, heart failure and congenital cardiology. He studied Medicine in Utrecht University and is a resident in cardiology at the University Medical Centre Utrecht, the Netherlands. Bram Ruijsink obtained a PhD at the department of Imaging Sciences and Biomedical Engineering at King’s College London in 2018, with his thesis focussing on the use of new exercise cardiac MR imaging, biomechanical modelling and artificial intelligence techniques to better understand heart failure in patients with congenital heart diseases. He currently works in a multidisciplinary research team of biomedical engineers at King’s College London to develop new artificial intelligence based tools to improve the diagnostic capabilities of cardiac imaging.

Chiara Nosarti is Professor of Neurodevelopment and Mental Health in the Department of Child and Adolescent Psychiatry at the Institute of Psychiatry, Psychology and Neuroscience and Head of Psychology and Outcome Studies at the Centre for the Developing Brain, King’s College London. Her research focuses on the study of neurodevelopmental outcomes in typically and atypically developing individuals across the life-span. She leads the follow-up of several longitudinal studies, including the Developing Human Connectome Project. Chiara uses multimodal neuroimaging in combination with cognitive, behavioural, social and environmental data in order to identify those children who are most vulnerable to psychopathology.

Dr Chris Dunsby is a joint lecturer between Photonics, Department of Physics and the Division of Experimental Medicine in the Department of Medicine at Imperial College London. His research interests are centred on the application of photonics and ultrafast laser technology to biomedical imaging and include multiphoton microscopy, multi-parameter fluorescence imaging and fluorescence lifetime imaging.

christopher.dunsby@imperial.ac.uk

Dr Chris Rowlands started his academic career in 2001 at Imperial College and studied for a PhD in the physics and chemistry of chalcogenide glasses at Cambridge University. After a year at the University of Nottingham, a Wellcome Trust MIT Postdoctoral Research Fellowship to the Massachusetts Institute of Technology and further time at Cambridge University, he joined Imperial’s Bioengineering Faculty in 2017. His current research is focused on the development of optical instrumentation, particularly for use in biological applications. Researchers in his group are pioneering new methods for imaging cancer, monitoring neural activity, quantifying microvascular blood flow, synthesizing new drugs, detecting chemical weapons and many other laudable goals. The lab has a flexible approach to new ideas and research outside the current fields of expertise, and actively tries to branch out into new fields wherever possible.

c.rowlands@imperial.ac.uk

Dr Christos Bergeles is a Reader in the Surgical & Interventional Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He received a PhD in Robotics from ETH Zurich, Switzerland, in 2011. He was a postdoctoral research fellow at Boston Children’s Hospital, Harvard Medical School, Massachusetts, and the Hamlyn Centre for Robotic Surgery, Imperial College, United Kingdom. He became a Lecturer (Assistant Professor) at UCL in September 2015, where he was a core-founding member of the the Wellcome EPSRC Centre for Interventional and Surgical Sciences. He joined King’s College London in July 2018 as a Senior Lecturer (Associate Professor). Dr.Bergeles received the Fight for Sight Award in 2014, an ERC Starting Grant in 2016, and an NIHR Invention for Innovation Grant in 2017. He is leading the Robotics and Vision in Medicine Lab (RViM), whose mission is to develop image-guided micro-surgical robots that assist the delivery of regenerative therapies deep inside the human body.

christos.bergeles@kcl.ac.uk

Dr Claudia Prieto is a Reader in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London.

Two major methodological challenges in Magnetic Resonance Imaging (MRI) are 1) image quality degradation due to physiological motion, and 2) long acquisition times. Both can lead to non-diagnostic image quality and a low patient throughput resulting in high operation costs if not adequately addressed. To cope with these problems her research has been focused on the development, implementation and application of undersampled motion corrected MRI technology. Undersampling reconstruction techniques allow speeding up the acquisition of MR images and/or improve image quality to satisfy clinical requirements. An important direction of her work is the combination of undersampled reconstruction techniques with motion correction strategies and the integration of prior information in the reconstruction process.

claudia.prieto@kcl.ac.uk

Dr Dafnis Batalle is a lecturer at the Institute of Psychiatry, Psychology & Neuroscience and the Centre for Developing Brain at the School of Biomedical Engineering & Imaging Sciences, contributing to both the Developing Human Connectome and AIMS-2-TRIALS projects.

Both a telecommunications engineer and a neuroscientist by training, Dr Batalle uses mathematical tools and computational models to study the emergence of brain organization during early development and how subtle alterations in key developmental processes lead to neurodevelopmental disorders such as autism and ADHD. He is particularly interested in the use of whole-brain computational models, graph theory, signal processing and machine learning tools to characterise brain networks and find early markers associated to atypical neurodevelopmental trajectories.

dafnis.batalle@kcl.ac.uk

Daniel Rueckert is Professor of Visual Information Processing in the Department of Computing at Imperial College London. His research group is interested in developing novel, computational techniques for the analysis of biomedical images. The group focuses on pursuing blue-sky research in methodology driven areas of biomedical image analysis, such as registration, segmentation and shape modelling. He is currently working on applications in biomedical image analysis and computing, machine learning in medical imaging, computer-aided diagnosis, computer-assisted therapy and interventions and clinical applications of medical image computing in neurology, cardiovascular and oncology. Read more about Daniel’s research.

d.rueckert@imperial.ac.uk

Dr David Carmichael is a reader in MRI in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He has a background in MRI Physics, which over time has developed into a wider interest in developing and applying new combinations of imaging techniques to measure and understand the human brain across spatial and temporal scales.

David has a particular interest in the application of these methods in the study of epilepsy. Modern neuroimaging play a number of vital roles in this context. They can be used to non-invasively identify (map) epileptogenic brain regions. However, they can also go far beyond this and be used to measure the complex interactions between brain areas and how these relate to the unwanted synchronous brain activity found in epilespy.
Crucially both the mapping and characterisation of brain dynamics can inform and assess treatment approaches for example via surgery or electrical stimulation.

david.carmichael@kcl.ac.uk

Professor David Edwards Professor of Paediatrics and Neonatal Medicine in the School of Biomedical Engineering & Imaging Sciences at King’s College London. The aim of the Centre for the Developing Brain is to reduce the incidence and severity of neurological impairment caused by problems around the time of birth. A bench to bedside research strategy has been developed to investigate the mechanisms of perinatal brain injury in order to find effective therapies, and have developed the first successful treatment for birth asphyxia, hypothermic neural rescue therapy.

There is a dedicated neonatal MRI suite cited in the neonatal intensive care unit of St Thomas’ Hospital to use imaging and neuroinformatic analysis to study brain development and damage.

ad.edwards@kcl.ac.uk

David Firmin is Professor of Biomedical Imaging at Imperial College London and the Physics Director of the Royal Brompton Hospitals CMR Unit. His involvement in Cardiovascular MR began in 1982 and he is one of the founding members of the Royal Brompton Unit which opened in 1984. His major contribution to MRI has been in the development of quantitative phase contrast velocity imaging. As the Director of Physics he has also led a number of pioneering advances in atheroma imaging, rapid and interactive cardiovascular MR, coronary angiography, myocardial perfusion imaging and tissue characterisation.

Professor Firmin has served on many scientific programme committees and in 1999 he organised a highly successful ISMRM Workshop on Flow & Motion in Cardiovascular MR and recently, in recognition of his service, he has been made a Fellow of ISMRM.  He is an Assistant Editor of the Journal of Cardiovascular MR, and a referee for several major international scientific journals, and a former panel member of the Wellcome Trust Infrastructure Grant.

Professor Firmin has more than 350 publications in cardiovascular MR imaging, including over 170 peer reviewed academic journal papers.

d.firmin@imperial.ac.uk

Dr David Nordsletten is a Reader in Cardiovascular Biomechanics at King’s College London. His principal emphasis in his research team is the integration of biomechanical modeling and advanced numerical techniques with clinical imaging.  This merger of disparate – yet mutually complementary – fields provides a new paradigm for analyzing and assessing health and disease, moving toward personalized patient care. Through the development of patient-specific mathematical models, they construct novel analysis tools to improve diagnosis, treatment and therapy planning in the heart. A key area of emphasis in their lab is the biomechanics of both healthy and failing hearts. Using biomechanical analysis software, they aim to characterize alterations in cardiac structure and function in disease.

david.nordsletten@kcl.ac.uk

David obtained his BSc from the University of Bristol in 2003, then completed an MPhil and PhD, both in organometallic chemistry, at the University of Southampton. He carried out postdoctoral research in main group materials chemistry with Claire Carmalt at UCL, before returning to Southampton to take up a role on the SCFED project with Gill Reid. In 2016 David moved to Imperial College London where he undertook a teaching and group management role for Paul Lickiss and, latterly, Tom Welton before starting at King’s as a lecturer in 2020. David’s research interests lie broadly in the area of inorganic transition metal chemistry, but he also has an interest in using inorganic materials as ion binders. In particular, binding radioisotopes such as 18F– within metal-organic frameworks for PET imaging purposes.

Professor David Sharp is a neurologist and an Associate Director of the UK Dementia Research Institute, where he leads the Care Research and Technology Centre. He is Deputy Head (Clinical) of the Centre for Restorative Neuroscience at Imperial College London and Scientific Director of the Imperial College Clinical Imaging Facility. His research programme aims to improve clinical outcomes after dementia and traumatic brain injury (TBI), focusing on common cognitive impairments in domains such as memory and attention. He uses cognitive neuroscience and advanced neuroimaging to investigate the effect of brain injury on brain network function and the effects of inflammation and neurodegeneration. His has explored how new treatments of cognitive impairment can be personalised and his current work focuses on harnessing neurotechnology development to improve the lives of those living with dementia and the effects of brain injury.

Declan O’Regan is Professor of Imaging Sciences at Imperial College London and head of the Computational Cardiac Imaging group at the MRC London Institute of Medical Sciences (LMS). His research work is funded by the NIHR, BHF, Bayer and the MRC, and he has published over 80 peer-reviewed papers including leading science journals. His multidisciplinary research focuses on applying machine learning to cardiovascular imaging to predict patient survival and model the effects of genetic variation on the heart.

Dr J-Donald Tournier is a Senior Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His work is focused on the development and application of diffusion MRI methods, particularly those that relate to the characterisation of brain white matter and its connectivity. White matter consists of the long-range axonal projections connecting between distinct areas of the brain, forming the communication backbone of the central nervous system. Diffusion MRI methods provide a way to estimate the large-scale ‘wiring diagram’ of the brain via fibre-tracking methods (a.k.a. tractography), and also to probe certain microscopic features of the tissue. Given the critical importance of white matter to normal and pathological brain function, such methods are becoming ever more widely used in brain studies. Donald has worked in many aspects of this rapidly evolving field, including the design of data acquisition schemes and sequences, the estimation of the fibre orientations, tractography algorithms to delineate the white matter pathways using this information, advanced methods for large-scale group comparisons, and clinical applications such as neurosurgical planning. He is currently involved in the protocol optimisation for the Developing Human Connectome Project, and investigating methods for the analysis of multi-shell HARDI data. Much of Donald’s research output is available for use in the open-source software package MRtrix, with the latest development efforts going into the next major release, MRtrix3.

jacques-donald.tournier@kcl.ac.uk

Dr Emma Robinson is a lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London, with interests focused on the application of machine learning techniques to improve understanding of human brain function and structure across the lifespan. She is centrally involved in the Human Connectome Project and Developing Human Connectome Project; these are big data initiatives designed to build models of human brain networks from thousands of Magnetic Resonance Imaging (MRI) data sets. The goal of these initiatives is to study how patterns of brain organisation vary across individuals, and to link these changes to differences in behaviour, cognition and genetics.
https://metrics-lab.github.io/

emma.robinson@kcl.ac.uk

Dr Enrico de Vita is a Reader in Medical Physics in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He has 14 years experience working as Magnetic Resonance Clinical Scientist in Medical Physics and Neuroradiology (National Hospital for Neurology and Neurosurgery). His main focus is in developing MRI acquisition and post-processing methods to provide novel imaging biomarkers, using these to establish natural history and measure response to therapy in proof-of-principle investigations of new treatments as well as elucidating underlying disease mechanisms. He has an interest in non-invasive MR quantification of cerebral perfusion with Arterial Spin Labelling (ASL), MR spectroscopy (MRS), high-field MRI and hybrid PET-MR technology.

New projects include investigating neonatal brain development at ultra-high field, optimisation of ASL acquisition and visualisation on PET-MR systems, and neonatal MRS.

enrico.devita@kcl.ac.uk

Eric Aboagye is Professor of Cancer Pharmacology & Molecular Imaging in the Department of Surgery and Cancer at Imperial College London, Director of the CRUK-EPSRC-MRC-NIHR Comprehensive Cancer Imaging Centre and head of the MRC-CSC Molecular Therapy group. His group is interested in the discovery and development of new methods for experimental and clinical cancer molecular imaging. In the past 5 years, the team has invented and translated three novel cancer diagnostics into human application. He has acted as an advisor to GE-Healthcare, GSK, Roche and Novartis.

eric.aboagye@imperial.ac.uk

Dr Fernando Zelaya is a Reader of Physiological Neuro-imaging at King’s College London. He has a a strong interest in physiological imaging such as cerebral blood flow and metabolism.

fernando.zelaya@kcl.ac.uk

Francesca Ciccarelli is Professor of Cancer Genomics at King’s College London and Group Leader at the Francis Crick Institute. Francesca graduated in Pharmaceutical Chemistry at the University of Bologna and received a PhD in Natural Sciences from the University of Heidelberg where she worked under
the supervision of Peer Bork at the EMBL. In 2005, Francesca started her independent research group at the European Institute of Oncology in Milan where she applied systems biology to study cancer. In 2014, she moved to King’s College London and since 2017 her group is seconded to the Francis Crick Institute. Francesca is co-lead of the patient stratification theme of the Cancer Research UK KHP Centre and of the cancer evolution theme of the CRUK City of London Cancer Centre. Francesca works with a multidisciplinary team of biologists, mathematicians, oncologists, engineers and computer scientists who apply molecular genetics, genetic and imaging data analysis and theoretical modelling to study cancer biology and evolution. The work in her lab is supported by Cancer Research UK, King’s Health Partners and the European Union.

Gareth Barker is Professor of Magnetic Resonance Physics in the Department of Neuroimaging within the Institute of Psychiatry, Psychology & Neuroscience at King’s College London. His research focuses on the application of Magnetic Resonance Imaging (MRI) to neurological and psychological disorders. It involves the development and testing of new image acquisition techniques, along with the processing and analysis approaches necessary to handle the data these create. He also works on optimisation of protocols to make these techniques applicable to patient populations.

Prof Barker has a particular interest in quantitative MRI techniques such as relaxation time measurement (which can be extended to allow assessment of brain myelin water fraction), magnetization transfer (again to probe white matter components such as myelin) and diffusion imaging (to investigate tissue microstructure); his current research focuses on “silent” methods for obtaining such data with greatly reduced acoustic noise.

gareth.barker@kcl.ac.uk

Prof Gary Cook is Professor of PET Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London. He trained in radiology and then nuclear medicine in London. He is a clinical academic in the Cancer Imaging Department, BMEIS, KCL and an honorary consultant at Guy’s & St Thomas’ Hospitals. Research interests include imaging bone metastases, measuring tumour heterogeneity, evaluation of novel tracers and biomarkers and refining multimodality imaging for diagnosis and response assessment in oncology.

gary.cook@kcl.ac.uk

Dr Gilbert Fruhwirth is a Lecturer in Imaging Biology in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Cell surface receptor interactions are emerging as a new regulatory level in cells providing signal diversity. They balance cellular equilibriums affecting fundamental processes such as motility, growth or senescence. Those processes are frequently deregulated in various human diseases including cancers.

As cancer cell metastasis is the major cause of cancer mortality, Dr Fruhwirth’s research team are especially interested in how cell surface receptor interactions and cellular processes regulating the latter affect metastasis. Therefore, they use genetic, biochemical, and biophysical approaches to unravel the underlying cellular mechanisms. They recently also identified the first link between over-expression and pro-metastatic mutation of the chemokine receptor CXCR4 and changes in the cellular lipidome.

Furthermore, they study metastasis pre-clinically on a whole-body level by using multi-modal multi-scale in vivo molecular imaging (radionuclide-fluorescence/bioluminescence-CT) to track cancer cells and their functional statuses. They are also interested in advancing in vivo imaging technologies suitable to study tumour biology and metastasis. For example, they developed the first fluorescence lifetime endoscope for quantifying protein-protein interactions or genetic biosensors and are currently continuing its development for specialist applications in cancers of unmet needs with a view of translating it into the clinic.

gilbert.fruhwirth@kcl.ac.uk

Dr Stasiuk is a Lecturer in Imaging Chemistry at King’s College London. His research includes design and synthesis of novel multimodal imaging agents for MRI, PET and Optical imaging. These include both small molecules and nanomaterials, based on inorganic complexes and semiconducting nanoparticles/quantum dots. The research is focussed on tools for image guided surgery and the development of “smart” theranostic imaging agents capable of monitoring drug delivery/efficacy, in cancer and cardiovascular disease.

graeme.stasiuk@kcl.ac.uk

Dr Sailem is Wellcome Career Development Fellow and the head of Biomedical AI and Data Science group at the School of Cancer and Pharmaceutical Sciences. She has extensive expertise in developing machine and deep learning approaches to automatically classify and analyse large-scale cellular and histopathological images. Her group focus on creating solutions for digital pathology and biomarker discovery from large biomedical data with focus on cancer. She is also interested in improving clinical trial design using AI. She manages number of projects funded by CRUK, MRC and EPSRC.

Before joining King’s, Dr Sailem worked between the Institute of Biomedical Engineering and Big Data Institute at the University of Oxford as a Sir Henry Wellcome Research Fellow and Corpus Christi Junior Research Fellow. There, she has developed several machine learning approaches to tackle challenges in pattern recognition and interpretability of large-scale biomedical image data.

Dr Sailem did her PhD at the Institute of Cancer Research in London where she developed methods for integrating phenotypic data with gene expression and modelling of the relationship between cell signalling and its context. She has a BSc in Computer Information Systems and MSc in Data Warehousing and Data Mining. Find out more on Dr Saliems’ website (www.hebasailem.com).

Dr Hongbin Liu is a Lecturer in Informatics (Robotics) in the Centre for Robotics Research Informatics at King’s College London.

hongbin.liu@kcl.ac.uk

Dr Isabel Dregely is a Lecturer in PET/MRI Acquisition & Reconstruction in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Her research interest is simultaneous PET/MR imaging. These hybrid systems have recently become available and promise a non-invasive comprehensive tissue characterization. However, the technology still faces the following limitations: 1) There is a mismatch between a complex multi-contrast MR vs. a simple “push-button” PET acquisition scan. 2) Patient motion during long scan acquisitions corrupts image quality. 3) There is no standardized procedure on how to combine the complex, multi-parametric information to generate clinically meaningful biomarkers of disease. To address these challenges, her research is focused on methods to integrate MRI and PET throughout acquisition, image reconstruction and post-processing. The clinical goals are to provide image-based quantitative information about the individual’s cancerous tissue biology to create opportunities to advance patient care.

isabel.dregely@kcl.ac.uk

Dr Jack Lee is Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. The major focus of his group is on characterising the pathophysiology of whole-heart cardiac perfusion and mechanics, and in order to address this, a combination of image & signal processing techniques, finite element analysis, and inverse parameterisation to patient-specific clinical data are employed. These models combined with advanced clinical imaging allow personalised modelling pipelines to diagnose disease, add refined interpretation to the medical data and predict outcomes of interventions. Read more about Jack’s research on his group’s website.

jack.lee@kcl.ac.uk

 

Dr James J Choi leads the Noninvasive Surgery & Biopsy Laboratory (www.nsblab.org) and is Lecturer (equivalent to Assistant Professor in the USA) in the Department of Bioengineering at Imperial College London.

The research aims of the Noninvasive Surgery & Biopsy Laboratory is to enable physicians to operate on vital organs using incision-less ultrasound-based microsurgical devices and methods. For patients, this implies not only accessible, painless, and infection-free techniques, but also potent therapeutic and diagnostic capabilities never achieved before. The laboratory’s current focus is on three research themes: 1) Drug Delivery using Molecular and Cellular Surgery, 2) Drug Distribution Enhancement using Fluid Micropumping, 3) Tissue Elasticity Imaging using Remote Palpation.

j.choi@imperial.ac.uk

Dr Wilton-Ely is a Reader in the Department of Chemistry at Imperial College London. He leads a group skilled in the synthesis of metal-based molecular compounds and nanomaterials as well as carrying out tissue culture and animal work.

Current research interests include molecular and nanoscale assemblies for use in MRI, PET and fluorescence imaging agent design. We are particularly interested in multimodal imaging and theranostics (DPT, PTT and encapsulated drug delivery. Our work on targeted, functionalised nanostructures combines MRI and optical imaging with light-driven therapy (PDT and PTT) for application to cancer diagnosis and therapy. A similar approach has been used to generate polygadolinium MRI contrast agents that targets tropoelastin, allowing the imaging of atherosclerosis. We also have an active research programme to develop probes for the selective sensing of the endogenous gasotransmitter, carbon monoxide (CO), in cells and in vivo. The production of this molecule in the body by heme oxygenase has implications for inflammation resolution and immune-suppression and we are investigating its modulation as a possible immunotherapy approach.

Read more about James’ research on his group’s website.

j.wilton-ely@imperial.ac.uk

Jana Hutter works in the Biomedical Engineering Department at King’s College London as a Sir Henry Wellcome Fellow.
Her PhD was awarded from the University Erlangen-Nuremberg in Germany where she developed in collaboration with Siemens Healthcare faster acquisition and reconstruction strategies for MR angiography. She joined King’s College London in 2014 and focuses since on quantitative multi-modal MRI techniques to study human development. She is involved in both the developing Human Connectome Project and the Placental Imaging Project.

Professor Jo Hajnal is Chair in Imaging Science at King’s College London. His research interests include in vivo imaging, particularly Magnetic Resonance Imaging (MRI), optical imaging and Ultrasound. A key theme has been integrating data acquistion with reconstruction and image analysis to acheive an integrated pipeline in which each element supports and is supported by the other key elements. Fetal imaging is a primary interest with major projects running to develop comprehensive fetal imaging methods incorporating new methods for both MRI and ultrasound. Read more about Jo’s research.

jo.hajnal@kcl.ac.uk

Dr Jonathan O’Muircheartaigh is a Wellcome Trust Henry Dale Fellow and an Honorary Senior Lecturer in the Department of Forensic and Neurodevelopmental Sciences within the Institute of Psychiatry, Psychology & Neuroscience at King’s College London. His primary research interests centre around clinical neuroimaging and developmental neuroanatomy.

Combining image registration and statistical techniques, he and his team build growth charts of typical and atypical brain development. Using these approaches, he and his team have been developing methods to quantify and localise brain injury and tissue abnormalities across a wide range of brain disorders, including multiple sclerosis, prematurity, and, in particular, childhood epilepsy. He collaborates with centres in Boston, Florida, Vancouver and London. He is also part of the European AIMs-2-Trials consortium focusing on the high co-occurrence of autism spectrum conditions and epilepsy (www.aims-2-trials.eu).

jonathanom@kcl.ac.uk

Jonathan Shapey is a Senior Clinical Lecturer at King’s College London and an Honorary Consultant Neurosurgeon at King’s College Hospital. Jonathan’s research is focused on the translational development of innovative healthcare engineering solutions for neurosurgery. His principal research interests include advanced intraoperative optical imaging technology and the application of artificial intelligence to guide patient management.

Jordi Alastruey is a Senior Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His lab specialises in cardiovascular haemodynamics. They study methods for cardiovascular function assessment based on the analysis of pulse wave signals using computational and experimental blood flow modelling, machine learning and deep learning, and clinical data, including medical images and data acquired by wearable sensors. The group has projects in a wide range of clinically relevant applications in collaboration with medical doctors, imaging scientists and mathematicians. See more about Jordi’s research on his group’s website.

jordi.alastruey-arimon@kcl.ac.uk

Dr Jorge Cardoso is a Senior Lecturer in Artificial Medical Intelligence in the in the Surgical & Interventional Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He leads a research portfolio on big data analytics and precision medicine. From a technical point of view, Jorge and his team have focused on the development of Artificial Intelligence based technical solutions to complex clinical problems in radiology, neurology, oncology and cardiology, learning from multi-source data, large scale diagnosis and prognosis, and operational predictions. Jorge also co-leads the development of NiftyNet (niftynet.io), an open-source deep-learning platform for artificial intelligence in medical imaging.

m.jorge.cardoso@kcl.ac.uk

Julia Schnabel is Chair of Computational Imaging in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Her research interests are in machine/deep learning, nonlinear motion modelling, multi-modality imaging, dynamic imaging and quantitative imaging for applications in cancer, cardiovascular diseases, and fetal health. Her focus is on developing mathematically principled methods for correcting complex types of motion, such as sliding organs, fetal movements, as well as imaging artefacts. She also has an interest in early disease detection, characterisation and prediction of response to treatment, with the aim of rapid translation into clinical practice for patient stratification and improved treatment outcome. Julia has over 25 years’ experience in medical imaging, has successfully supervised 20 PhD students to completion, and is leading a large research group at King’s, in close collaboration with Imperial.

Visit Julia’s public profile.

Get in touch: julia.schnabel@kcl.ac.uk

Kawal Rhode is Professor of Biomedical Engineering and Head of Education in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research team develops novel technology-based solutions to healthcare problems, particularly heart disease. Solutions are developed by his multi-disciplinary team and in partnership with clinicians at St. Thomas’ hospital and a number of international industrial partners. Examples of current work include clinically-useful quantification of medical images, development of image-guided solutions for cardiac interventions, development of catheter and imaging robots, computer-based automation of analyses and interventions and development of tele-health solutions. Read more about Kawal’s research.

kawal.rhode@kcl.ac.uk

Professor Ashkan is the lead for Functional and Oncological Neurosurgery at King’s College Hospital. His clinical practise covers the 4.5 million population of South East London and Kent, translating into around 300 operations per year. He heads the Neurosciences Clinical Trial Unit at King’s and is the Deputy Lead for the King’s Neurosciences Research Advisory Group. He is the President of the British Society for Stereotactic and Functional Neurosurgery. He is the Lead for the Glioma Genomics England Clinical Interpretation Partnership Section of the100K Genomes Project.
Prof Ashkan’s main clinical and research interest include deep brain stimulation, basal ganglia anatomy and physiology, intra-operative imaging and physiology, image guided surgery, immunotherapy, brain tumour genomics, minimally invasive neurosurgery, radiosurgery, new and novel therapies and patient reported outcome measures. He has published over 400 full papers, abstracts and book chapters. He is the Associate Editor of the British Journal of Neurosurgery. In 2018 he was voted Clinician of the Year nominated by the Brain Tumour Charity.

Kirsten Christensen-Jeffries received the B.Sc. degree in maths and physics from the University of Warwick, Coventry, U.K., in 2010, and the M.Res. degree in Bioimaging Sciences with Imperial College London, London, U.K., in 2011.

She spent eight months working with IXICO, London, in 2011/2012. She received the Ph.D. degree from King’s College London, London, U.K., in 2016. In 2019, she was awarded an MRC Career Development Award which is currently being undertaken within the Ultrasound Imaging Group, Kings College London, London. Her research interests include ultrasound and contrast enhanced ultrasound imaging, with a focus on image and signal analysis of ultrasound data, artefact correction, and the development of super-resolution ultrasound imaging techniques for visualisation of the microvasculature.

Dr Kogularamanan “Rama” Suntharalingam is a Lecturer in Bioinorganic Chemistry in the Department of Chemistry at King’s College London. His research group is broadly interested in bioinorganic chemistry, chemical biology, biotherapeutics, molecular biology, and nanotechnology. Work in the group aims to use the structural, optical, redox, magnetic, and catalytic diversity offered by metal-containing molecules to design and develop new generations of (bio)chemical tools to diagnose and treat diseases. The group also focuses on engineering new bioinspired nano-material systems for medical diagnosis and treatment.

kogularamanan.suntharalingam@kcl.ac.uk

Dr Laura Peralta is a Royal Society University Research Fellow in the Department of Biomedical Engineering at King’s College London. Her research interests range from fundamental ultrasound studies to clinical applications, including ultrasound propagation in complex media, beamforming methods, quantitative ultrasound, and tissue characterisation. A key part of her ongoing research addresses advanced ultrasound imaging and functional measurements. Her long-term objective is to advance the state-of-the-art of medical ultrasound and contribute to screening, monitoring, and prevention methods.

Dr Lefteris Livieratos is a Clinical Scientist (Medical Physicist) at Guy’s & St Thomas’ Hospitals and Senior Clinical Lecturer in Imaging Sciences at King’s College. He worked in PET methodology at the MRC Cyclotron Unit, Imperial/Hammersmith on image-based quantification where he developed novel schemes for patient motion correction. He subsequently worked as clinical scientist in diagnostic and therapeutic applications of nuclear medicine, including the clinical implementation of the first SPECT/CT in Europe with diagnostic multi-slice CT.

He is actively involved in teaching and supervision of students and trainee clinical scientists. His research interests include multi-modality imaging, quantification, tracer kinetics and dosimetry for translational applications and molecular radiotherapy.

lefteris.livieratos@kcl.ac.uk

Mads is a lecturer in biophotonics in the Craniofacial Development and Stem Cell Biology division of the Faculty of Dentistry, Oral & Craniofacial Sciences at King’s College London. He received his MSc. Degree in Engineering, Physics and Technology (optics) from the University of Southern Denmark and his Ph.D. in Biomedical Engineering (Bioimaging) from National University of Singapore. He was awarded the Marie Curie Fellowship at Imperial College London and the United Kingdom Regenerative Medicine Platform (UKRMP) Special Merit Prize. He is currently a Lecturer in Biophotonics at Kings College London. He has published over 28 original research papers. His research interests include biomedical optics and light-tissue interaction, linear/non-linear optical spectroscopy/imaging, advanced endoscopy and artifical intelligence. He holds several commercialized patents in healthcare.

mads.bergholt@kcl.ac.uk

Dr Malene Fischer is a consultant in Nuclear Medicine and Clinical Senior Lecturer at King’s College London. The common thread of her research is the exploration and implementation of hybrid imaging, PET/C and PET/MR, in diagnosing and treatment of patients with cancer, literally from lab to bed-side including cost-effectiveness analysis. Dr. Fischer has supervised (completed): 4 PhD, 1 Post-Doc, 9 masters, 7 bachelors and 2 specialist courses and are currently supervising 5 PhD-students. Her research is based on multi-disciplinary collaboration and she has supervised medical students as well as students of biomedical engineering and physics. More than 500 hours of pre-graduate teaching and lecturing at several national and international post-graduate courses.

Marc Modat is a senior lecturer in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research interests cover amongst others the development of novel imaging biomarkers especially for neurodegenerative diseases. He has significant expertise in medical image registration as well as in medical image segmentation and machine learning. He is also promoting the translation of state-of-the-art engineering solutions to clinical research and clinical practices.

marc.modat@kcl.ac.uk

Dr Maria Deprez works in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Her research topic is motion correction in fetal brain MRI and she also participates in the Developing Human Connectome Project.

She graduated from the Faculty of Mathematics, Physics and Informatics at Comenius University, Bratislava. Her PhD was awarded by the Department of Computing, Imperial College London, where she worked on image analysis of Infant brain MRI. During her postoc at Imperial, she worked on neonatal brain MRI. At the Institute of Biomedical Engineering at the University of Oxford, she developed automatic image analysis tools for fetal brain Magnetic Resonance Images and Ultrasound.

maria.murgasova@kcl.ac.uk 

Dr Marietta Charakida is Senior Clinical Lecturer and Honorary Consultant in Fetal and Paediatric Cardiology at Evelina Children’s Hospital and King’s College Hospital. Her research has focused on determining how risk factors such as obesity, hyperlipidemia, inflammation can contribute in the initiation and progression of arterial disease in the young. Her current research interest involves unraveling maternal, fetal and postnatal factors which contribute to development of cardiovascular disease by using advanced imaging modalities starting from fetal life. She is also working on establishing lifestyle modification strategies which can impact on the quality of life of patients with congenital heart disease.

Dr Marina Kuimova is a Reader in Chemical Physics in the Department of Chemistry at Imperial College London. Her research interests include elucidation of biologically relevant processes using different types of fluorescence imaging and time-resolved spectroscopy.  Her current work uses variety of imaging and spectroscopic techniques to elucidate the nature of processes involved in cell function and death, including those during Photodynamic Therapy (PDT) treatment of cancer.

m.kuimova@imperial.ac.uk

Mark Green is Professor of Nanoimaging in the Department of Physics at King’s College London. His research interests include organometallic based synthesis of semiconductorand metal nanoparticles, biological applications of nanomaterials, rare-earth based nanomaterials.

Professor Green received his BSc from Manchester Metropolitan University in 1995 and his PhD from Imperial College London in 1998.  He was a post-Doctoral fellow at Imperial College from 1998-99 and at the University of Oxford from 1999-2000. He worked as a Scientist at Oxonica Ltd from 2000-2004 and then joined King’s College as a lecturer in Bio-nanotechnology in 2007. He became a Senior Lecturer in 2007, a Reader in 2009 and a Professor in 2014.

mark.a.green@kcl.ac.uk

Dr Martin Bishop is a Reader in Computational Cardiac Electrophysiology in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses on Computational Cardiac Electrophysiology. He uses high-resolution, multi-model imaging data, from both the clinic and the experimental lab, to construct very detailed computational models of the heart, further parameterised with functional experimental measurements. These models are then used within state-of-the-art cardiac simulation environments to conduct in-silico experiments probing hitherto unknown mechanisms of the functioning of the heart in both health and disease. Specifically, his research examines the mechanisms underlying how and why the normal, synchronised electrical activation of the heart may break-down into highly disorganised ‘arrhythmic’ behaviour, in order to develop better preventative and therapeutic measures.
Read more about Martin’s research

martin.bishop@kcl.ac.uk

Martin Wilkins is Professor of Clinical Pharmacology and Vice Dean for Research at Imperial College London. For the past 25 years he has led a bench-to-bedside programme investigating the molecular basis of pulmonary hypertension and evaluating new treatments. Prof Wilkins’ work, supported throughout by the British Heart Foundation, contributed to the development of two new classes of drug for pulmonary hypertension, namely phosphodiesterase inhibitors and soluble guanylate cyclase stimulators, and more recently provided insights into the roles of iron and zinc in pulmonary vascular homeostasis.

Prof Wilkins was elected to the UK Academy of Medical Sciences in 2015. He holds a Liebig Professorship at the Justus Liebig University of Giessen (since 2014). He was awarded honorary membership of the Kyrgyz National Academy of Sciences (2013). He is Past-President of the Pulmonary Vascular Research Institute, a global network of experts in the field (www.pvrinstitute.org).

Mary Rutherford is Professor of Perinatal Imaging at King’s College London. Seh trained as a paediatrician, specialising in neonatal neurology. She has worked with magnetic resonance imaging (MRI) for over 30 years. Her expertise is in the acquisition and interpretation of fetal and neonatal MRI of the brain. Her research interests include optimising MR sequences to allow objective quantification of both normal and abnormal brain development.

She is employed by King’s College London and has an Honorary contract with Guys and St Thomas’ NHS Foundation Trust (GSTT).

Dr Maya Thanou is a Reader in Nanotechnology at the Institute of Pharmaceutical Science, King’s College London. She finished her PhD in LACDR (Leiden/Amsterdam Centre for Drug Research). She took her first academic appointment in the School of Pharmacy, Cardiff University as Lecturer in Polymer Therapeutics and Drug Delivery. In 2004 she was awarded the prestigious Dorothy Hodgkin Royal Society Research Fellowship and she continued research at Imperial College, at the Department of Chemistry. She moved on at King’s College London in 2009. She is the director of Msc Pharmaceutical Technology programme and leads research in the field of image guided drug delivery. Her research fouses on engineering image-guided cancer targeted nanoparticles, as novel drug delivery devices. She has published a number of academic articles and one book on this topic and she is the main or co-inventor of several patents. She is the co-founder of AJMmedicaps a diagnostics’ startup.

maya.thanou@kcl.ac.uk

Professor Mengxing Tang is a Chair Professor in Biomedical Imaging in the Faculty of Engineering at Imperial College London. His research focuses on developing new ultrasound imaging and computational technologies, and their applications in cardiovascular diseases, cancer, and neurology. Particularly his research focuses on leveraging the large amount of data afforded by ultrafast acquisition (>kHz frame rate) to achieve high image resolution and contrast. His team, with collaborators at KCL and ICL, have been the first to demonstrate in vitro and in vivo acoustic super-resolution imaging, breaking the conventional wave diffraction limit, by localising and tracking microbubble contrast agents. Professor Tang’s team is also working on applying deep learning to various aspects of ultrasound imaging to improve the image quality and speed. He works with a range of clinical collaborators including cardiologists, radiologist, clinical oncologist, cancer surgeons, and neurologists.

mengxing.tang@imperial.ac.uk

Dr. Miaojing Shi is a Lecturer in Artificial Intelligence at the Department of Informatics, King’s College London. He received his PhD in image processing from Peking University, in 2015. He was with University of Oxford between 2012 and 2013 working on visual neuroscience; and with INRIA Rennes working on visual search between 2014 and 2015. He was a postdoctoral researcher at University of Edinburgh and became a research scientist at Inria Rennes since Dec 2017. He joined King’s College London in January, 2020. His research field is computer vision and machine learning. His current focus is visual learning and understanding with limited supervision, which covers weakly-supervised learning, semi-supervised learning and few-shot learning etc. He applies his research in visual search, object detection, medical image segmentation etc.

Michael Bronstein (PhD 2007, Technion, Israel) is a professor at Imperial College London in the Department of Computing, where he holds the Chair in Machine Learning and Pattern Recognition and Royal Society Wolfson Merit Award. He holds/has held visiting appointments at Stanford, Harvard, MIT, and TUM. Michael’s main research interest is in theoretical and computational methods for geometric data analysis. He is one of the pioneers of deep learning on graphs and manifolds. He is a Fellow of IEEE and IAPR, ACM Distinguished Speaker, and World Economic Forum Young Scientist. He is the recipient of multiple prestigious awards, including four ERC grants, two Google Faculty awards, and the 2018 Facebook Computational Social Science award. Besides academic work, Michael was a co-founder and technology executive at Novafora (2005-2009) developing large-scale video analysis methods, and one of the chief technologists at Invision (2009-2012) developing low-cost 3D sensors. Following the multi-million acquisition of Invision by Intel in 2012, Michael has been one of the key developers of the Intel RealSense technology in the role of Principal Engineer. His most recent venture is Fabula AI, a startup dedicated to algorithmic detection of fake news using geometric deep learning.

m.bronstein@imperial.ac.uk

Dr Michelle Ma is a lecturer in Imaging Chemistry within the School of Biomedical Engineering & Imaging Sciences at King’s College London. Michelle’s research focuses on synthesising and testing new chelators for coordination of radioactive metal isotopes (including 68Ga, 99mTc, 64Cu, 213Bi, 89Zr, Al-18F, and 188Re) that are used in whole body diagnostic SPECT or PET molecular imaging, or in radiotherapy. These novel chelator systems allow for facile incorporation of a metallic isotope into biomolecules such as peptides, proteins, nanoparticles and other targeting vectors, thus providing versatile tools for in vivo targeting of radioactivity to tumour tissue. Such platforms/enabling technologies are essential to widespread adoption of radiometallic medical isotopes in hospitals and clinics, and are key to providing ready access to the largest number of patients.
Michelle’s projects combine inorganic chemistry, synthesis, radiochemistry and in vitro and in vivo studies, with a view to translating new chemical platforms to clinical application.

michelle.ma@kcl.ac.uk

Professor Molly M Stevens is Professor of Biomedical Materials and Regenerative Medicine and the Research Director for Biomedical Material Sciences in the Department of Materials, in the Department of Bioengineering and the Institute of Biomedical Engineering at Imperial College London. Her research focuses on developing innovative materials and characterization techniques for applications in healthcare. Prof Stevens has contributed a rich portfolio of smart biomaterials with targeting, delivery and image contrasting functions for applications as imaging probes, biosensors and drug delivery vehicles. Her research exploits specific biomolecular recognition and self-assembly mechanisms to create new dynamic nano-materials. She has developed innovative materials characterisation techniques for investigating bio-nanomaterials, 3D cell cultures and tissues, and the cell-material interface.
Prof Stevens graduated with a First-Class Honours BPharm degree from Bath University (1995) and a PhD from the University of Nottingham (2001). After postdoctoral research at the Langer group at MIT, she joined Imperial College London as a lecturer in 2004 and was promoted to Professor in 2008. She is Director of the UK Regenerative Medicine Platform Smart Materials Hub, Deputy Director of the EPSRC IRC in Early-Warning Sensing Systems for Infectious Diseases and President of the Royal Society of Chemistry Division of Materials Chemistry. She is Fellow of the Royal Society, the Royal Academy of Engineering and Foreign Member of the National Academy of Engineering.

m.stevens@imperial.ac.uk

Dr. Nazila Kamaly’s research is highly multidisciplinary and uses bioinspired chemical approaches to synthesise multi-functional polymeric nanomedicines, nanodiagnostics or nanotheranostics capable of changing their surface or core properties in response to local or up-regulated disease markers for stimuli-responsive and spatiotemporally controlled biological drug delivery. Her lab also investigates nanomedicine bio-efficacy using microfluidic and lab-on-a-chip systems as in vitro and ex vivo biomimetic models with controlled environmental parameters for testing nanoparticle physicochemical properties. This facilitates a more dynamic biological mechanistic insight between nanoparticles and target cell populations. Dr. Nazila Kamaly has been a lecturer in the Chemistry department at Imperial College London since April 2019. Before this she was an Associate Professor at the Technical University of Denmark, Department of Micro and Nanotechnology, where she was awarded a prestigious Lundbeck Fellowship in 2016 to establish her research group. Prior to this she was an Instructor and postdoc in the Laboratory of Nanomedicine and Biomaterials at Harvard Medical School (2011-2015) and the Laboratory of Prof. Robert Langer at MIT (2011-2015), where she pioneered anti-inflammatory polymeric nanomedicines for heart disease therapy. Prior this she carried out postdoctoral research at Imperial College London Chemistry Department (2007-2010), where she developed nanomedicines, nanodiagnostics and nanotheranostics for oncology applications. She obtained an MSci degree in Medicinal Chemistry from University College London (2002), and a PhD in Bioorganic Chemistry from Imperial College London, Department of Chemistry (2008). 

Dr Neal Bangerter is a Reader in Magnetic Resonance Physics in the Department of Bioengineering at Imperial College London. He received a Bachelor’s degree in Physics from U.C. Berkeley, and Master’s and Ph.D. degrees in Electrical Engineering from Stanford University. His doctoral studies were conducted under the supervision of Dr. Dwight Nishimura and Dr. John Pauly, both pioneers in pulse sequence development and signal processing in MRI. Prior to joining Imperial, Dr. Bangerter spent a decade in the Department of Electrical & Computer Engineering at Brigham Young University, where he founded and directed the BYU Magnetic Resonance Imaging Research Laboratory. His research focuses largely on the development and optimization of new MR imaging techniques at high and ultra-high main polarizing field strengths (3 and 7 Tesla) to a variety of applications, with a recent focus on musculoskeletal applications and the in vivo assessment of cartilage health.

n.bangerter@imperial.ac.uk

Dr Niamh Nowlan is a Reader in Developmental Biomechanics in the Department of Bioengineering at Imperial College London. Dr Nowlan’s research programme applies engineering approaches to advance our understanding of fetal and neonatal skeletal development and health. Key areas of interest are a) the role of fetal movement in joint shape development, with particular relevance to a common postnatal hip abnormality DDH, b) the role of fetal movements in development of the spine, with relevance for congenital scoliosis, and c) quantifying normal and abnormal fetal movements as an indicator of fetal wellbeing. Dr Nowlan has received a number of prestigious awards, including a New Investigator Recognition Award from the Orthopaedic Research Society, and the 2016 Bioengineering Society UK Early Career Scientist Award, while a recent study from her lab received the 2018 S.M. Perren Award of the European Society of Biomechanics for best scientific paper. Dr Nowlan’s research is funded by an ERC Starting Grant (€1.5 million), and grants from EPSRC, the Anatomical Society and the Royal Society.

n.nowlan@imperial.ac.uk

Nick Long is Professor of Inorganic Chemistry at Imperial College London. The Long Group has expertise in applied synthetic inorganic and organometallic chemistry. Research interests focus on transition metal and lanthanide chemistry for the synthesis of functional molecules, homogeneous catalysis and in recent years, probe design and novel methodologies for biomedical imaging. Professor Long is also Deputy Director of the CDT.

n.long@imperial.ac.uk

Dr Oleg Aslanidi is a Senior Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His main research interests are in computational modelling of the heart and cardiac arrhythmias, as well as imaging modalities that enable the reconstruction of the 3D heart structure in health and disease. Despite a vast amount of clinical data from patients and cell to organ level experiments, complex arrhythmogenic mechanisms in the entire heart remain unclear. Computational modelling provides a quantitative framework for integrating multimodal imaging and experimental data in-silico. Validated computational tools can be applied for dissecting patient-specific arrhythmia mechanisms and predicting optimal treatments, and therefore can assist in clinical decision-making. Read more about Oleg’s research.

oleg.aslanidi@kcl.ac.uk

Dr Olena Rudyk is a Lecturer, Principal Investigator and Group Leader in the School of Cardiovascular and Metabolic Medicine & Sciences at King’s College London. She received PhD in Physiology from the Bogomoletz Institute of Physiology in the National Academy of Sciences in Ukraine in 2006. She joined the Cardiovascular Department at King’s soon after and held British Heart Foundation Intermediate Basic Science Research Fellowship from 2015 to 2020.

Dr Rudyk has 15 years of integrative cardiovascular research experience, including ten years of cardiac ultrasound imaging. Having developed an interest in pulmonary hypertension during her Fellowship, she continues her research on understanding the molecular mechanisms contributing to this devastating disease. Her work, supported by the British Heart Foundation, seeks to identify novel redox sensors and signalling pathways, employing an integrative approach to test potential new targets for therapy.

Dr Rudyk employs serial in vivo medical imaging modalities, including ultrasound and Doppler flow, to assess cardiopulmonary function alongside ex vivo and in vitro assessments. Her lab is also exploring using state-of-the-art photoacoustic ultrasound imaging to study animal models of cardiopulmonary and cardiovascular disease. Ultimately, Dr Rudyk’s work aims to help translate findings from preclinical studies into the clinic and bridge the gap between basic research and clinical applications.

olena.rudyk@kcl.ac.uk

Dr Özlem Ipek is a lecturer in ultra-high Field MRI engineering at the Department of Biomedical Engineering within the School of Biomedical Engineering & Imaging Sciences at King’s College London. After completing physics (METU, Turkey) and applied physics degrees (TU/e, Netherlands), she received her PhD degree in 2014 from Utrecht University, Netherlands. She was a scientist and managing director of the RF lab at EPFL, Switzerland before moving to KCL. Her research interest is in developing, designing and prototyping MRI hardware for 7 Tesla MRI scanner and clinical MRI scanners for body and neuro imaging. She supervised over 12 student projects, 3 master thesis and several PhD students including one as an official co-supervisor. She has over ten years of experience on 7 Tesla MRI parallel-transmit RF technology and MRI safety management.

ozlem.ipek@kcl.ac.uk

Prof. Pablo Lamata is a Wellcome Trust Senior Research Fellow at King’s College London. His research interest focuses in the combination of imaging and computational modelling technologies to improve the management of cardiovascular diseases. He develops solutions to stratify subjects according to the remodelling of cardiac anatomy, to characterise the performance of the heart during diastole, and to assess non-invasively the pressure driving blood flow. His team (cmib.website) has developed solutions for the identification of faulty valves, for the detection of growth differences caused by pre-term birth, or for the optimal patient selection for ablation or resynchronization therapies, among others. He coordinates the EU consortium “Personalised In-Silico Cardiology” (picnet.eu) that develops modelling methodologies to optimize clinical protocols, from data acquisition to device parameters and intervention choices.

pablo.lamata@kcl.ac.uk

Dr Paul Bentley is Clinical Senior Lecturer and Honorary Consultant Neurologist within Centre for Restorative Neurosciences, Imperial College London. After training at Cambridge and UCL, he undertook a research fellowship in Psychology Dept, Harvard, and a PhD in cognitive neuroscience at UCL. He was awarded a Stroke Association Clinical Fellowship and DoH New Blood Award. He is the first UK neurologist to have been dually-accredited in stroke medicine by the Royal College of Physicians.

Dr Bentley’s research group is developing bedside computerized tests, devices and neuroimaging techniques that can profile stroke patients, and assign them individually to their optimal acute and restorative personalised therapies.

Dr Paul Edison is a Clinical Senior Lecturer in the Division of Brain Sciences at Imperial College London and an honorary Professor at Cardiff University, Wales. He is also a Consultant Physician at Hammersmith Hospital, London.

Dr Edison’s research has focused on neuroimaging with novel molecular probes using PET and magnetic resonance techniques for imaging pathophysiological changes associated with Alzheimer’s disease, Parkinson’s disease, and other neurodegenerative diseases. He has extensive experience in PET imaging in different neurodegenerative and neuroinflammatory conditions. His initial work evaluated one of the first amyloid imaging agent in Alzheimer’s disease at the MRC Cyclotron Unit at Hammersmith Hospital, and has published seminal papers in the field. Combined with his clinical expertise in different types of degenerative diseases and dementia, he has investigated the relationship between amyloid deposition, microglial activation, and glucose metabolism in different disorders, along with evaluating different transporters in the brain. His work in assessing microglial activation and amyloid load showed that both of these are increased in Alzheimer’s disease, and microglial activation correlates with cognition in late stages of the disease, while amyloid load does not correlate with cognition. His investigation into the longitudinal trajectory of Alzheimer’s disease has demonstrated that there are two peaks of microglial activation in the Alzheimer’s trajectory, and proposed that the early peak could be protective, while the later peak could be detrimental in the disease trajectory.

He is now evaluating the relationship between microglial activation, tau formation and neuronal function. His work focuses on neuroinflammation, and the interplay between inflammation and immunity in neurodegenerative and neuroinflammatory disease, and relating these with genetic information. He is also evaluating the methods of modulating inflammation and amyloid in Alzheimer’s disease, and the influence of cardiometabolic factors on the development of neurodegenerative diseases by means of clinical and pre-clinical studies.

Following on from the evaluation of cardiometabolic factors, he is now evaluating the influence of GLP-1 analogues in the treatment of Alzheimer’s disease and other neurodegenerative diseases. He is leading a multicentre intervention study, evaluating liraglutide in Alzheimer’s disease, coordinating 24 research sites.

He has published in high Impact journals such as Brain, Annals of Neurology, Neurology, and has received grants from the Medical Research Council, NIHR/HEFCE, Alzheimer’s Society, Alzheimer’s Research UK, Alzheimer’s Drug Discovery Foundation US, and other funders. He has also received grants from Novo Nordisk, GE Healthcare, Novartis, Piramal Life Sciences and Astra Zeneca.
He has received an MRC clinical research fellowship award, HEFCE clinical senior lecturership award, and research scholarships. He has also received several best paper awards internationally, and published in leading scientific journals. He supervises PhD, MSc and BSC students, and runs a laboratory focussing on neuroimaging and cardiometabolic and genetic factors, and novel interventions in treatment of Alzheimer’s disease.
He is a reviewer for MRC, EPSRC, BBSRC, Alzheimer’s Association International, Alzheimer’s Research UK, Alzheimer’s Society, and several other funding agencies. He is also a reviewer for major journals.
He leads the Imperial College Memory Research Centre, and is the Chief Investigator of several imaging and intervention studies using PET and MRI, and heads multicentre studies evaluating novel treatment for Alzheimer’s and other neurodegenerative diseases. He also runs a memory clinic at Imperial College Healthcare NHS Trust.

Professor Paul French is Head of Photonics Group at Imperial College London. He was a Physics undergraduate at Imperial in 1980 and has continued as a PhD student, post-doctoral researcher and member of the academic staff.  He has also worked as a Visiting Professor at the University of New Mexico and as a Consultant at AT&T Bell Laboratories, Holmdel, NJ.  His research interests have evolved from ultrafast dye and solid-state laser physics to interdisciplinary biomedical optics-based research including coherence-gated imaging through turbid media and fluorescence lifetime imaging (FLIM) for applications in molecular cell biology, drug discovery and clinical diagnosis. His current research includes the development of multidimensional fluorescence imaging for microscopy, endoscopy and tomography. Paul is currently Head of the Photonics Group in the Physics Department and may be contacted via the Optics Office. Read more about Paul’s research.

paul.french@imperial.ac.uk

Paul Marsden is Professor of PET Physics at King’s College London. He led the early development of combined PET and MRI multimodality imaging systems and his research interests include all aspects of PET imaging from detectors and imaging systems through to data acquisition and analysis methods for clinical and research PET studies. Much of this involves collaborating with clinicians and scientists in oncology, cardiology and neuropsychiatry. As Director of Medical Physics at Guy’s and St Thomas’ PET Centre Paul is familiar with the regulatory, logistical and technical issues associated with PET imaging. He is co-lead of the UK PET Core Lab and General Chair of the 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference.

Read more about Paul’s research.

paul.marsden@kcl.ac.uk

Paul Matthews is the Edmond and Lily Safra Chair and Head of Brain Sciences in the Department of Medicine at Imperial College London. His research has addressed related themes. He has extended applications of advanced imaging methods to answer a new range of clinical research questions. He collaborated closely with Oxford colleagues (especially Professor S. Smith) in applications developments for advanced structural and functional brain imaging incorporated into the open access FSL software distributed by the FMRIB Centre, now one of the two most widely used image analysis software “toolboxes” worldwide. While at Imperial and GSK, his group (then including Professor T. Nichols, now at the University of Warwick) piloted approaches extending these methods for the first properly controlled, prospectively designed imaging genetics studies.  Over the last 5 years, he has been Chair of the Imaging Working Group for UK Biobank, which is pioneering an ambitious programme for very large population imaging as part of the UK Biiobank (Prof Sir Rory Collins, CEO). MRI scanning of the brain, heart and body, along with DEXA and 3D carotid ultrasound, was initiated in a dedicated imaging centre at UK Biobank’s Cheadle (Manchester) site in May, 2014.

Professor Matthews’ work to develop the underpinning methods has focused on applications in drug development and disease outcomes monitoring. His former, GSK-based, research group harnessed the tools particularly for experimental clinical neuroscience drug development. Their approach linked physiology pharmacology and involved introducing and validating new PET radioligands and integrated PET/fMRI pharmacokinetic and pharmacodynamic studies with more conventional early phase clinical development outcomes.

An overarching application has been to address the challenge of neurodegeneration in Multiple Sclerosis (MS) and enhancing intrinsic brain repair and plasticity for functional recovery. More recent collaborative work with Imanova Ltd. builds on studies of the genetics and pharmacology of the latest generation of PET microglial imaging agents to relate microglial activation and neurodegeneration in vivo.

Dr Periklis (Laki) Pantazis is a Reader in Advanced Optical Precision Imaging (equiv. Associate Professor) at the Department of Bioengineering at Imperial College London.

He studied Biochemistry at the Leibniz University of Hannover, Hannover/Germany followed by a PhD in Biology and Bioengineering at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany.

He pursued then postdoctoral studies at the California Institute of Technology/Pasadena/CA/USA before joining as an Assistant Professor the ETH Zurich Department of Biosystems Science and Engineering in Basel/Switzerland.

In 2018/2019, he established his Laboratory of Advanced Optical Precision Imaging at Imperial College London that conceives and applies cutting-edge imaging technologies, assays and reagents for the mechanistic dissecting of development, disease progression and tissue regeneration. His team fosters interdisciplinary projects in the fields of Developmental and Stem Cell Biology, Engineering, Chemistry and Optics.

p.pantazis@imperial.ac.uk

Peter Weinberg is Professor in Cardiovascular Mechanics in the Department of Bioengineering at Imperial College London. His research is chiefly concerned with elucidating mechanisms involved in the development of atherosclerosis. He has developed a new theory relating the anatomically patchy distribution of atherosclerosis to variation in blood flow, endothelial nitric oxide synthesis and uptake of plasma macromolecules by the arterial wall. He is also developing methods of pulsewave analysis for assessing nitric oxide synthesis non-invasively, and is studying the large differences in vascular fluid mechanics that occur between species of different size. The work has been funded by BBSRC, EPSRC, MRC, BHF and the Wellcome Trust.

p.weinberg@imperial.ac.uk

Professor Phil Blower is Chair in Imaging Chemistry within the School of Biomedical Engineering & Imaging Sciences at King’s College London. The chemistry challenge in the Blower group is to design and construct the radiopharmaceuticals and to develop highly efficient chemistry for radiolabelling with the utmost speed and simplicity of manipulation. The biological behaviour of the new probes is evaluated in tissue culture and small animal imaging en route to clinical translation. The range of chemistry encompasses metal complexes, proteins, peptides and nanoparticles. Many radionuclides, spanning the whole periodic table, are studied including Tc-99m, Cu-64/62/61, Ga-68/67, In-111, Zr-89, C-11, F-18, N-13, Re-188, I-123/131/125, Ra-223, Lu-177, Y-90 and others, and the applications cover cancer, neurosciences, cardiovascular, musculoskeletal, cell tracking and immunological areas.

philip.blower@kcl.ac.uk

Dr Phil Miller is a Lecturer in Radiochemistry at Imperial College London. His research interests include rapid synthetic chemistry for the preparation of short-lived radioactive carbon-11 (t1/2 = 20 min) and fluorine-18 (t1/2 = 110 min) tracer molecules for PET imaging and the application of microfluidic reactors to small scale chemical reactions,  gas-liquid phase reactions and improving radiochemistry processes.  He is also interested in novel ligand design for coordination chemistry, transition metal catalytic C-C coupling reactions and imaging sciences.

philip.miller@imperial.ac.uk

Dr Po-Wah So (@powahso) is Senior Lecturer in Biomedical Imaging and Spectroscopy, Head of the Phenomics Lab in the Department of Neuroimaging at the Institute of Psychiatry, Psychology and Neuroscience (IoPPN) at King’s College London.

Dr So has a BSc in Medicinal Chemistry (University College London) and a PhD in Chemistry (Birkbeck College, University of London) and nearly 30 years of experience in biomedical applications of nuclear magnetic resonance spectroscopy (NMR), and magnetic resonance imaging and spectroscopy (MRI and MRS).

Initially, Dr So specialized in NMR-based metabolomics of liver disease. She then went on to develop MRI-based molecular and cellular imaging; investigate lifestyle interventions in peripheral metabolic disease e.g., obesity, non-alcoholic fatty liver disease, in preclinical models; and biological substrates underlying quantitative MRI signals in neurodegenerative diseases at Imperial College. Since joining King’s in 2008, Dr So has focused on the role of metals, especially iron, in brain ageing and Alzheimer’s Disease, and the complex interplay between neurodegenerative and peripheral metabolic diseases. She has been awarded funding from UK research councils; charities including The Wellcome Trust, Alzheimer’s Research UK, and various companies including Agilent Technologies.

Dr So is Secretary of the British Chapter of the International Society of Magnetic Resonance in Medicine (BCISMRM); co-lead of ‘Emerging Imaging’ in the EPSRC CDT Smart Medical Imaging; Department of Neuroimaging Admissions Tutor; and Leader of the module ‘Practical Neuroimaging’ for MSc Neuroimaging. She primary and co-supervises many PhD and MSc student projects (> 30).

po-wah.so@kcl.ac.uk

 

Prof Prashant Jha is Head of Affordable Medical Technologies within the School of Biomedical Engineering & Imaging Sciences at King’s College London. He is an editor, inventor and serial entrepreneur who trained in medicine, bioengineering, product design, computer science, strategy and innovation management. As a serial entrepreneur, he has set venture-backed businesses in the domains of vaccine delivery, personalized oncology, internet services, education technology and medical devices over the last fifteen years. He has co-invented eight medical devices in the areas of stress urinary incontinence, haemorrhoid surgery, labour monitoring, stroke detection, pulmonary medicine and diabetes management. He has appointments at medical, engineering and business schools in Japan, Australia, India and Europe – with whom he works to create a global ecosystem for developing low-cost, high-impact medical devices. As a medical editor, he serves as the Senior Editor for The BMJ and is the co-founder and editor of BMJ Innovations, world’s first medical innovations journal focused on devices, diagnostics, and digital health.

prashant.jha@kcl.ac.uk

Dr Rachel Sparks is a Lecturer in Surgical and Interventional Engineering at the School of Biomedical Engineering & Imaging Sciences, King’s College London. The primary focus of her research is on developing computer assisted planning and image-guided navigation techniques to increase accuracy of targeting pathologic structures and improve safety during surgical treatments. This work involves building patient-specific models of anatomy, and using these models to provide quantitative measures of risk and efficacy related to surgical interventions, including the placement of tools, removal or thermal treatment of tissue. Ongoing work in her group is focused on using deep learning to improve the ability identify and delineate important structures of interest within the brain (e.g. vasculature, white matter tracts, and pathology) as well as to simulate tissue response to surgical interventions. These techniques are translated into the clinical as part of the Epilepsy-Navigator (EpiNavTM) software platform to provide clinical tools for the diagnosis and treatment of epilepsy.

rachel.sparks@kcl.ac.uk

Dr Rafael T.M. de Rosales is a Lecturer in Imaging Chemisty at King’s College London. His research includes design and synthesis of novel medical imaging agents (small molecules, peptides and nanoparticles) based on metallic radionuclides (e.g. 64Cu, 99mTc, 89Zr); non-invasive detection of lymph node metastases using PET-MRI and bimodal nanoparticles; and the development of “smart” imaging agents capable of measuring biological processes in vivo.

rafael.torres@kcl.ac.uk

Professor Ralph Sinkus is Chair in Bioengineering at King’s College London. His current research activities are mainly focused on the assessment and the understanding of biomechanics within the human body for disease characterization and therapy efficacy evaluation by using MR and ultrasound elastography. This interest goes far beyond the “plain” measurement of tissues’ viscoelastic properties, but reaches out into fundamental physics such as for instance anomalous wave propagation in fractal-like media and apoptotic cellular processes triggered via mechanotransduction.

The 4 main stream research foci in order to complement and extend the current research portfolio in the bioengineering group at King’s:

• Fundamental physics of waves in scattering hierarchical media encompassing acoustics (shear and compressional waves) as well as electromagnetic waves (RF and light);
• Broadband biomechanical modelling of the human heart via MR-elastography: assessing the viscoelastic, poroelastic and anisotropic mechanical properties of the myocardium;
• Translational studies aiming at bringing novel mechanical imaging biomarkers to the patient for early diagnosis, intervention planning, and therapy;
• Interaction of waves with cells: how can mechanotransduction steer the fate of a cell?

ralph.sinkus@kcl.ac.uk

Ramón Vilar is Professor of Medicinal Inorganic Chemistry and is currently Head of the Chemical Biology research section in the Department of Chemistry at Imperial College London. His research focuses on medicinal inorganic chemistry, chemical biology, molecular recognition and self-assembly and molecular imaging

r.vilar@imperial.ac.uk

Dr Ran Yan is a Lecturer in PET Radiochemistry at King’s College London. His research focuses on the development of novel radiopharmaceuticals for cardiovascular disease, neural degenerative disease and cancer diagnostics. These 18F and radioactive iodine labeled tracers are based on fluorescent aromatic compounds with the potential for multimodality multiscale imaging with optical and nuclear techniques. He is also interested in developing new methodologies for small organic molecules labeling with no carrier added 18F.  Read more about Ran’s research.

ran.yan@kcl.ac.uk

Rene Botnar is Professor of Cardiovascular Imaging at King’s College London. His research group is working on the development of novel MRI acquisition methods and protein/cell specific contrast agents for morphological, functional and biological imaging of atherosclerosis, coronary artery disease, post infarct remodeling and cancer. To account for respiratory and cardiac motion, to improve quantification and visualization of contrast agent accumulation and tissue characterization, they develop novel motion compensation techniques, blood and tissue specific MRI prepulses and T1/T2* mapping techniques. Biological processes that they are investigating include endothelial dysfunction, inflammation, matrix remodeling and thrombosis. New projects include preclinical PET/MRI of atherosclerosis and myocardial infarction.

rene.botnar@kcl.ac.uk

Professor Reza Razavi is Vice President & Vice-Principal (Research & Innovation) King’s College London and Director of Research at King’s Health Partners. He is also the Leader of the Imaging and Biomedical Engineering Clinical Academic Group, Professor of Paediatric Cardiovascular Science at King’s College London and Consultant Cardiologist at Guy’s and St Thomas’. Professor Razavi qualified in Medicine at St. Bartholomew’s Medical School in 1988. He later trained in Paediatrics and Paediatric Cardiology and started a research career following his clinical training. His research is in imaging and biomedical engineering related to cardiovascular disease. One key area of focus is cardiac MRI in relation to congenital heart disease, electrophysiology and heart failure, image guided intervention, XMR (X-ray and MRI) guided cardiac catheterisation and methodological advances to move to faster 3-Dimensional cardiac imaging.

Dr Rick Southworth is a Lecturer in Cardiac Molecular Imaging at King’s College London. His research group has two main aims – to utilise new imaging techniques to understand cardiac biology, and to use our understanding of cardiac biology to develop new imaging techniques.  They use high field NMR imaging and spectroscopy, and PET and SPECT imaging to characterise the biochemistry of the heart during health and disease. They then use traditional biochemical assays (and less traditional ones like immunogold electron microscopy) to provide biochemical context to the data that imaging techniques provide. Current projects include development of imaging agents for cardiac metabolism, hypoxia, mitochondrial toxicity, platelet activation and free radical production. Read more about Rick’s research.

richard.southworth@kcl.ac.uk

Dr Robert Leech is a Senior Lecturer within the Division of Brain Sciences at Imperial College London and is a member of the Computational, Cognitive and Clinical Neuroimaging Laboratory. His research is inherently multi-disciplinary, integrating neuroscience, psychology and computer science to better understand the healthy and pathological brain. Visit Imperial’s website to read more about his research.

r.leech@imperial.ac.uk

Prof Roger Gunn is currently Chief Scientific Officer – Neuroscience at Invicro and Professor of Molecular Neuroimaging at Imperial College. He has combined a career in academia (McGill University, Oxford University and Imperial College) and industry (GSK, Imanova and Invicro) which focusses on advancing healthcare through medical imaging.

He is originally an applied mathematician whose research interests involve the application of mathematical biology and molecular imaging techniques to disease understanding and drug development. His research has led to the discovery and development of novel imaging biomarkers along with algorithms and software for their effective deployment in clinical imaging trials.  He has held executive management positions in industry for the last 10 years with responsibility for a wide range of scientific imaging portfolios. He is also the founder and a director of MIAKAT Ltd which develops image analysis software for PET imaging data.

r.gunn@imperial.ac.uk

Dr Rosalyn Moran is a reader of theoretical neurobiology in the Department of Neuroimaging at King’s College London.The research in her lab focuses on Computational Neuroscience, Computational Psychiatry and Computational Neurology. In particular, her team aims to join together brain connectivity analysis with the putative algorithmic role of why regions in the brain are connected and what information these connections relay. This work lies at the intersection of Artificial Intelligence (deep networks), Bayesian Inference (variational principles) and Experimental Neurobiology (cognitive tasks in the scanner, with eye tracking and/or M/EEG). Of particular interest to these questions are the role of families of neurotransmitters in algorithmic deployment – e.g. the role of noradrenaline in prediction errors and model-based decision making. We use the Free Energy principle as a principle to develop new methods in Artificial Intelligence and in disease modelling. Diseases of interest include age-related neurodegenerative disease and schizophrenia.

Previously her lab was based at the University of Bristol at the department of Engineering Mathematics and prior to that at Virginia Tech. Dr Moran serves as an editor for Neuroimage and Neuroimage Clinical.

rosalyn.moran@kcl.ac.uk

Dr Samantha Terry is a Senior Lecturer in Radiobiology in the School of Biomedical Engineering & Imaging Sciences at King’s College London. Her research interests are to understand how radionuclides used for therapy and imaging affect cells and to use this knowledge to help create better radiopharmaceuticals or imaging tracers. The radionuclides of specific interest are those emitting alpha particles and Auger electrons as they deposit their energy within the range of only a few cells.

The work carried out includes experiments using isolated DNA, whole cells, clusters of cells, in vivo work such as tumour response monitoring and imaging, and ex vivo analysis of damage to tumour cells and healthy tissues. The techniques used are also very varied; they encompass methods to determine DNA/chromosomal damage and repair, cell viability and killing, cell cycle alterations/influences, localization of the radionuclide and autoradiography. Overall, studies are a nice mix of techniques usually used in targeted radionuclide therapy and imaging, radiobiology, and molecular and cellular biology.

Follow Samantha on Twitter: @syaterry

samantha.terry@kcl.ac.uk

Dr Sam Powell is a Senior Lecturer in the School of Biomedical Engineering & Imaging Sciences at King’ s College London, and holds a Royal Academy of Engineering Fellowship. His principle research interests involve the development of ‘hybrid’ medical imaging techniques, such as ultrasound-modulated optical tomography, which employ ultrasound and near-infrared light to probe the function and morphology of biological tissues. These ‘coupled-physics’ methods have a broad range of applications ranging from functional neuroscience to the identification of malignant tumours.

Sam originally trained as an electronic engineer, and continues to maintain close links to industry. His approach to research is holistic, ranging from the development of electronic hardware, the use of high performance computing to build models of the physics underlying hybrid imaging modalities, and the study of the inverse problem by which clinically relevant images are reconstructed from measured data.

s.powell@kcl.ac.uk

Dr Sanjay Prasad is a Consultant Cardiologist at the Royal Brompton Hospital and Reader at Imperial College. He graduated from Cardiff University and undertook postgraduate training in London, Harvard and Geneva.

His areas of expertise include magnetic resonance imaging (MRI), cardiomyopathy (heart muscle disease), heart failure and ischaemic heart disease.

Prof Seb Ourselin is Head of the School of Biomedical Engineering & Imaging Sciences at King’s College London, which is dedicated to the development, clinical translation and clinical application of medical imaging, computational modelling, minimally invasive interventions and surgery. He is Director of the Wellcome / EPSRC Centre for Interventional and Surgical Sciences and the EPSRC Image-Guided Therapies UK Network+ and has raised over £40M as Principal Investigator, including £10M under the Innovative Engineering for Health initiative to create the GIFT-Surg project.

He is co-founder of Brainminer, an academic spin-out commercialising machine learning algorithms for brain image analysis. Their first product, DIADEM, a clinical decision support system for dementia diagnosis, is CE marked and medically approved.

He has published over 400 articles and is an associate editor for IEEE Transactions on Medical Imaging, Journal of Medical Imaging, Nature Scientific Reports, and Medical Image Analysis. He has been active in conference organisation (12 international conferences as General or Program Chair) and professional societies (APRS, MICCAI). He was elected Fellow of the MICCAI Society in 2016.

Previously, he was based at UCL where he had numerous affiliations including Director of the Institute of Healthcare Engineering and the EPSRC Centre for Doctoral Training in Medical Imaging, Vice-Dean (Health) for the Faculty of Engineering Sciences, Head of the Translational Imaging Group within the Centre for Medical Image Computing (CMIC) and Head of Image Analysis at the Dementia Research Centre (DRC). Before joining UCL, he founded and led the CSIRO BioMedIA Lab, Australia. He led the imaging research programme of the AIBL study and of a successfully commercialized colonoscopy simulator.

Dr Sebastien Roujol is a Lecturer in the Biomedical Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His broad research interests is on the development of novel cardiac MRI methods and image processing algorithms to assess patient pathologies and monitor clinical treatments. One of his main focus is to develop new methods to plan and monitor ablation procedures of cardiac arrhythmias. This work includes novel developments for quantitative/qualitative myocardial tissue characterization for assessment of the cardiac arrhythmogenic substrate, multi-modal co-registration of MRI and electrophysiology data for procedure planning, real time MRI-guidance for ablation lesion assessment.

sebastien.roujol@kcl.ac.uk

Serena Counsell is a Professor of Perinatal Imaging & Health in the School of Biomedical Engineering & Imaging Sciences at King’s College London.  Her primary research focus is the use of diffusion MRI to assess tissue microstructure, functional MRI and other neuro-informatic tools to assess neonatal and paediatric brain development and injury, and to develop MR imaging biomarkers to provide outcomes for trials of neuroprotective therapies.

serena.counsell@kcl.ac.uk

Dr Shaihan Malik’s research focuses on the physics of MRI, particularly in imaging using ultrahigh field (7T) MRI systems. Shaihan leads a program of methods development for the recently installed 7T London Collaborative Ultrahigh field System (LoCUS). Although 7T systems can achieve much higher spatial resolutions than their lower-field clinical counterparts, the high frequency RF fields required can result in non-uniform image contrast and signal, which limits clinical utility. Parallel transmission RF technology can be used to improve the achievable image quality, but is currently largely limited to experimental use; largely this is due to safety concerns and problems with work-flow. Shaihan’s research is focused on solving these problems to take this technology into routine use. He has received funding from the EPSRC as an Early Career Fellow to work in this area. A related research theme is that of safe interventional MRI, and he has received funding from the MRC DPFS scheme to build new prototype technology.

Another area of research activity is in the development of quantitative MR techniques. This includes development of new mathematical modelling methods, and measurement methods that account for complex tissue microstructure.

For further information see Shaihan’s profile on Research Gate and for open source code see mriphysics.github.io.

 

Sonia Nielles-Vallespin is a Senior Lecturer of Cardiovascular Magnetic Resonance physics at the National Heart and Lung Institute, Imperial College London. Her research interests lie in CMR, specifically in vivo Diffusion Tensor CMR (DT-CMR) to study the microstructural dynamics of cardiac contraction. In vivo DT-CMR offers huge potential for technical innovation and it may provide novel insights into microstructural abnormalities of regional cardiac function inaccessible by any currently available clinical test.

Dr Sophie V Morse is a Research Fellow in the Department of Bio engineering at Imperial College London and leads the Ultrasound Cell Stimulation laboratory.

The research aims of her lab are to develop ultrasound technologies to modulate the activity of cells, by either activating or inhibiting them, to aid the diagnosis and treatment of brain diseases. Current research interests include in Vivo testing and detection of imaging probes delivered to the brain using focused ultrasound blood-brain barrier opening, the detection of activated or inhibited activity of brain cells, and imaging changes in immune cells activity in brain tumours following ultrasound treatments.

Project: Noninvasive molecular biopsy: focused ultrasound delivery of targeted contrast agents and detection by magnetic resonance imaging

Since 2005 Spencer Sherwin has been a Professor in Computational Fluid Mechanics in the Department of Aeronautics at Imperial College London and currently holds a research chair supported by McLaren Racing/Royal Academy of Engineering. Sherwin leads a successful research group focussing on the development and application of parallel spectral/hp element techniques for solving partial differential equations (www.nektar.info). This has particularly focussed on the application of these techniques to biomedical flow modelling at multiple levels of the cardiovascular system ranging from modelling the whole systemic cardiovascular system to localised modelling of cellular-level transport and electrophysiological modelling (www.imperial.ac.uk/bioflows). In doing so he works closely with clinicians, biologists and medical physicists and has published joint papers and obtained joint funding in a number of relevant research areas.

s.sherwin@imperial.ac.uk

Prof Steve Williams is the Founder, Director and Head of the Centre for Neuroimaging Sciences based at the Institute of Psychiatry and Maudsley Hospital, King’s College London. His work focuses on the translation of imaging techniques from bench to bedside with an emphasis on the development of new tools for diagnosis and prediction of response to treatment. He was the University of Cambridge’s first PhD in Magnetic Resonance Imaging (MRI) and he then went on to set up a University of London-wide Intercollegiate Imaging facility which focused on the development and application of magnetic resonance techniques in a wide range of pre-clinical models of disease. In 1994, he moved to the Institute of Psychiatry to champion the application of neuroimaging in disorders of the central nervous system and has co-authored over 400 papers in leading neuroscience journals.

steve.williams@kcl.ac.uk

Steven Niederer is Professor of Biomedical Engineering in the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research is characterised by the use of multi-scale and multi-physics computational models of the heart to investigate fundamental physiological questions and gain insight into patient pathologies and treatments. This work includes the development of novel methods for integrating and interpreting patient data, evaluating new medical devices using computational modelling and developing patient specific models. His research is highly interdisciplinary, working closely with imaging scientists, basic researchers and cardiologist with a strong focus on clinical translation.

steven.niederer@kcl.ac.uk

Prof Sven Plain is a British Heart Foundation Professor of Cardiovascular Imaging and honorary Consultant Cardiologist. He studied Medicine in Marburg/Germany and received an MD from the Phillips University in Marburg/Germany in 1995 and my PhD from the University of Leeds in 2004. Prof Plein was previously a British Heart Foundation Senior Clinical Research Fellow (2011-2015), Wellcome Trust Intermediate Research Fellow (2006-2010) and British Heart Foundation Junior Research Fellow (2001-2003). He has held several societal positions including Vice presidency European Association of Cardiovascular Imaging (EACVI) of the European Society of Cardiology, Chairman of the Working Group on Cardiovascular Magnetic Resonance Imaging of the European Society of Cardiology and serves on several editorial boards.

Prof Plein’s main research interest is magnetic resonance imaging (MRI). He focuses on developing and validating novel MRI methods and apply them to disease models and patients studies in order to answer clinically relevant questions. A particular aim of his group has been the development and clinical translation of myocardial perfusion MRI. More recently, his work has focussed on cardiometabolic disease, in particular the effects of diabetes mellitus on the cardiovascular system.

Dr Tevfik Ismail is a consultant cardiologist at Guy’s and St Thomas’ and a clinical senior lecturer at King’s College London. He has specialist interests in cardiovascular magnetic resonance imaging; heart failure; inherited and inflammatory heart muscle disease.

He is part of the inpatient heart failure service at St Thomas’ hospital and works closely with the Bexley community heart failure service, running a monthly clinic at Queen Mary’s hospital, Sidcup. He has authored/co-authored numerous original papers in high impact international journals including Journal of the American College of Cardiologists, Circulation, Journal of the American Medical Association, Heart and the Journal of Cardiovascular Magnetic Resonance among others.

Dr Thomas C Booth is a Senior Lecturer in the Department of Neuroimaging at King’s College London and an Honorary Consultant Diagnostic and Interventional Neuroradiologist at King’s College Hospital. His interests are in neuro-oncology imaging (including advanced MRI techniques and machine learning), neurovascular (aneurysm treatment; stroke imaging patient stratification); and incidental finding research (deep learning abnormality detection). Much of his focus is on brain tumour treatment response assessment using brain tumour MRI – he is reminded continuously how important neuro-oncology diagnostics are when presenting patients at the neuro-oncology multi-disciplinary team meetings in a busy London teaching hospital.

He sits on the National Cancer Research Institute Brain Tumour Committee, the Royal College of Radiologists Academic Committee and the Royal College of Radiologists AI Policy Reference Group. He was recently awarded the inaugural Royal College of Radiologists Outstanding Researcher Award.

thomas.booth@kcl.ac.uk

Dr Tim Witney is a Wellcome Trust Senior Research Fellow and Senior Lecturer in the Department of Imaging Chemistry and Biology within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His multidisciplinary group develops next-generation imaging tools to monitor therapeutic response and detect drug resistance. Currently, there is no satisfactory way to identify patients that are refractive to the standard of care. Positron emission tomography (PET) imaging offers a potential solution to this clinical problem through the non-invasive assessment of molecular processes that underpin acquired drug-resistance. This precision medicine approach will enable the clinician to adapt the patient’s treatment regimen upon the emergence of resistance. If successfully implemented, this strategy has the potential to dramatically improve disease outcomes whilst providing substantial cost savings for the healthcare system.

tim.witney@kcl.ac.uk

In April 2006, Professor Schaeffter took up the post as the Philip Harris Professor of Imaging Sciences at King’s College London. A major aim of his current research is the investigation of novel MR-techniques for cardiac, interventional and quantitative MRI. One aspect of his work is the investigation of novel MR-techniques for 4D-acquisitions and motion modelling. In particular, whole-heart MR-acquisitions are investigated to simplify cardiac MRI by reducing the required user interaction during scanning. This technique is also important for creating roadmaps used in image-guided interventions. An important topic is the creation of motion models to correct for respiratory motion. These models have also been applied for motion compensated PET reconstruction using simultaneously acquired PET and MR-data. Another important topic is the development of quantitative MR techniques for diagnosis and for characterisation of treatment effects.

His research interests include Magnetic Resonance Imaging (MRI) particularly new sequences and reconstruction techniques for rapid MRI; interventional MRI and devices; motion modeling and motion compensation in MRI; simultaneously PET/MRI; quantitative MRI; cancer MRI; and cardiac MRI.

tobias.schaeffter@kcl.ac.uk

Dr Tom Eykyn is a Lecturer in the Imaging Chemistry & Biology Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research team are developing hyperpolarisation techniques for enhancing the MRI signal of 13C or 15N. Using the technique of Dynamic Nuclear Polarization (DNP) they are able to amplify the signal by many orders of magnitude and to develop real-time techniques for measuring metabolic conversion of a number of biological molecules in cell suspensions, whole perfused organs or in vivo. The rates of these metabolic processes can act as potential biomarkers of a range of pathophysiologies and subsequently in response to treatment. Current projects include studies of altered cardiac bio-energetics in perfused hearts in response to ischemia/ reperfusion.

He is also interested in altered glycolytic metabolism in cancer, both in cultured cells and in tumours and subsequent response to chemotherapeutic agents. Further to this he develops solution state NMR experiments, novel 13C labelled probe molecules as well as fast sequences for real-time metabolic imaging. In related projects they have a joint program collaborating with the University of Sheffield in hyperpolarised 3He lung imaging to compare ventilation heterogeneity in asthmatics vs normal patients.

Read more about Tom’s research.

thomas.eykyn@kcl.ac.uk

Tom is Professor of Interventional Image Computing within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research focuses on translational medical image computing and machine learning with a specific interest in their applications to surgery and interventional sciences.

Prior to this, Tom was Associate Professor at University College London (UCL) where he acted as Deputy Director for the Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS). In his previous industrial tenure at Mauna Kea Technologies, he served as New Technologies Manager to identify emerging technologies and support their acquisition within the company and led the company image computing group. Tom received his PhD, co-supervised by Nicholas Ayache and Xavier Pennec at Inria Sophia Antipolis, in 2008 from Ecole des Mines de Paris. He obtained his Master of Science in Electrical Engineering at Columbia University in 2004 and graduated from Ecole Polytechnique in 2003.

tom.vercauteren@kcl.ac.uk

Dr Tom Arichi is a MRC Clinician Scientist and Clinical Senior Lecturer in the Department of Perinatal Imaging. His current work aims to apply non-invasive imaging techniques (EEG, functional MRI and simultaneous EEG-fMRI) to characterise the development of functional activity in the human brain, during fetal and preterm life and following brain injury. He also holds a visiting position in the Human Robotics group at Imperial College London, where they are developing novel tools for use in the MRI scanner and automated rehabilitative strategies for young infants who have suffered brain injury.

tomoki.arichi@kcl.ac.uk

Tony Gee is Professor of PET and Radiochemistry in in the Imaging Chemistry & Biology Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London and a visiting Professor at the Department of Chemistry, Imperial College London. In terms of research, a number of very active research projects are in progress including the development of rapid labelling synthetic techniques with short-lived positron-emitting radionuclides, small molecule-protein / small molecule-membrane interactions, the design of PET imaging probes, and the understanding of in vivo pharmacology.

antony.gee@kcl.ac.uk

Professor Vicky Goh is the Chair and Head of Department of Cancer Imaging in the School of Biomedical Engineering & Imaging Sciences at King’s College London and Consultant Radiologist at Guy’s and St Thomas’ Hospitals NHS Foundation Trust. She chairs the Academic Committee of the Royal College of Radiologists, is past President of the European Society of Oncologic Imaging, Fellow of the European Society of Abdominal and Gastrointestinal Radiology, and on the Steering Committee of the European School of Radiology. She is on the Editorial Board (Deputy Editor) of Radiology.

Her research focuses on multimodality functional imaging and biomarker development in cancer with a special interest in gastrointestinal, lung and urological cancers. She has >150 peer reviewed papers. She has given >50 national/international keynote lectures and has an international reputation for translating novel functional imaging techniques into clinical practice. She is an active contributor to National/International practice guidelines and policy.

vicky.goh@kcl.ac.uk

Dr Abbate is a Senior Lecturer in the Department of Analytical, Environmental and Forensic Sciences within the Faculty of Life Sciences & Medicine at King’s College London. He currently leads a vibrant research group composed of 2 PDRA and 8 PhD students and is the Programme Director for the MSc in Analytical Toxicology.

Dr Abbate’s research is multidisciplinary and of a collaborative nature, and lies primarily in the area of bioanalysis, underpinned by his expertise in analytical science & synthetic chemistry, and his research supports two critical themes in the field: a) Mass Spectrometry (MS)-based bioanalysis for the detection of drugs, metabolites and other biomarkers in biological matrices, and b) the design of smart diagnostic/theragnostic probes.

Dr Wenfeng Xia a Lecturer in the Surgical & Interventional Engineering Department within the School of Biomedical Engineering & Imaging Sciences at King’s College London. His research is centred on the development and clinical translation of novel medical devices to improve patient outcomes during surgical and interventional procedures. One area of research focus is photoacoustic imaging, an emerging modality that provides rich optical contrast with highly scalable spatial resolution and penetration depth, proven to have great potential for many pre-clinical and clinical applications. A second area of focus is ultrasonic tracking to identify the tip of medical device during many ultrasound image-guided minimally invasive procedures.

wenfeng.xia@kcl.ac.uk

Dr Wenjia Bai is a lecturer jointly affiliated with the Department of Computing and Department of Brain Sciences at Imperial College London. His research focuses on developing novel image computing and machine learning algorithms for medical image analysis and applying the algorithms to clinical research, including medical image segmentation, registration, atlas construction, motion tracking and motion analysis. Currently, he is actively involved in several population-level large-scale imaging studies including the UK Biobank Imaging Study and UK Digital Heart Project. Read more about Wenjia’s research.

w.bai@imperial.ac.uk

 

I graduated with a Bachelor of Technology in Industrial Engineering from Delhi Technological University, India, in 2019. I had the opportunity to conduct a research internship at the University of New South Wales, Australia where I worked on Diabetic Retinopathy detection. Through the internship, I was exposed to the need for early detection of diseases through the use of technology and found my passion in Healthcare Technologies. I worked as a Machine Learning Engineer at a HealthTech startup in India for a year and later worked as a Research Assistant at Rochester Institute of Technology and Stanford University, where I developed a keen interest in building a HeathTech startup of my own. Combining these experiences led me to pursue this a PhD at the CDT in Smart Medical Imaging, which will enable me to translate my research into practice. I will be investigating Diffusion Models and Geometric Deep Learning to simulate fetal brain growth for early detection of diseases.

Project: Deep Generative Models of Fetal Brain Development: forward modelling of the mechanisms of neurodevelopmental impairment

I graduated with a Master’s degree in Computer Science from a French engineering school, EPITA, in 2018, with a major in AI and Deep Learning. After graduating, I started working at Siemens Healthineers, where I applied my knowledge to Image-Guided Interventions. This allowed me to gain some valuable work experience and understand the challenges faced by industry in the clinical world. Seeing the benefits of AI in healthcare, I decided to pursue a PhD with King’s in 2021. Currently, my research focuses on combining robotics and AI to automate certain tasks in the interventional room.

I began my research career as a physicist, obtaining my Bachelors from the University of Cambridge and an MSc in Physics from King’s College London. I was then enrolled on the Centre for Doctoral Training in Quantum Technologies at UCL, obtaining an MRes in Quantum Technologies researching Quantum Machine Learning. Seeking something more practical, I spent 6 months as a research intern with Siemens Healthineers’ AI team, and soon returned to King’s as a DTP student researching Imaging Genetics under the supervision of Dr Emma Robinson. I am currently focused on researching neonatal brain surfaces with graph convolutional networks.

Project: Engineering big data solutions to mining imaging genetics data through deep learning

Originally from Bangladesh, I graduated with a First Class BSc (Hons) in Computer Science from Middlesex University London in 2019. I developed a keen interest in Deep Learning during my final year research project where I analysed the different components of the Cycle Consistent Generative Adversarial Networks (Cycle GAN) in the domain of unpaired image style transfer. Then I moved to Canberra to pursue my Masters in Machine Learning and Computer Vision at the Australian National University, where I had the opportunity to continue my work on GANs in multiple projects. In one of the projects titled ‘ArtGAN’, I developed a novel generator architecture for conditional image generation, which was very deep in terms of layers but had far less parameter count compared to the state of the art. For my master’s research project, I used GANs to filter out specified features from EEG brainwave signals given an input condition, which can be thought of as conditional domain transfer. During this project, I developed an interest to further explore the role of Artificial Intelligence methods related to human Physiology.
The EPSRC CDT in Smart Medical Imaging’s Doctoral Training program particularly interested me as it offered the chance to further enhance my domain knowledge through the MRes year and apply those skills throughout the course of the Ph.D. My Ph.D. focuses on the human heart’s right ventricle’s role in risk prediction following mitral valve replacement, which is a combined imaging-modelling study.

Project: The right ventricle’s role in risk prediction following mitral valve replacement: a combined imaging-modelling study

I graduated in 2019 with an MEng in Biomedical Engineering from King’s College London where I was fortunate enough to work on various projects during my studies. These ranged from novel applications of machine learning algorithms for improvement of current neuroimaging techniques to computational modelling of cardiac mechanics during atrial fibrillation. The study of cardiac arrhythmias and their effects on stroke risk soon became my primary research interest and the opportunity to continue this work was an exciting prospect. I believe that my PhD project will allow me to develop my understanding of cardiac disorders through computational modelling of fluid dynamics to improve patient outcomes for these prevalent diseases.

Project: Stroke risk in a “healthy” patient

I graduated from the University of Leicester in 2018 with a BSc (Hons) in Medical Biochemistry. In my final year I was fortunate enough to undertake a research project with Prof John W Schwabe, where I investigated the novel class I histone deacetylase (HDAC) complex, MiDAC, and its role in chromosome alignment during prometaphase.
Following my undergraduate degree, I came to King’s College London for an MSc in Biomedical and Molecular Research. It was at this point that I was first introduced to imaging biology and chemistry. I worked under the supervision of Dr Ran Yan to produce radio-iodinated dual modality imaging reagents, suitable for antibody conjugation and PET/fluorescence guided tumour surgery.
This CDT is an incredible programme as it is intrinsically interdisciplinary, spanning the sciences and engineering. This programme will enable me to develop an array of techniques, in collaboration with supervisors and peers, to produce insightful and impactful research.

Project: Imaging the Warburg effect with ²³Na MRI and ⁸²Rb positron emission tomography

I completed my Integrated Masters in Chemistry from Centre of Excellence in Basic Science at University of Mumbai, India with my Master thesis at UBC, Vancouver, Canada. During my thesis with Hafeli group at UBC, I worked on “Synthesis of an Alzheimer Imaging agent: A theranostic model”  and also during my previous research projects based on Imaging, I got exposed to different imaging techniques like MRI and PET-CT in particular and chemical and biological imaging in particular. I picked up a keen interest in radiolabelling and the theranostic approaches to imaging agents via these projects.
This Medical Imaging CDT program appealed to me because of its program structure in the form of core, stream and interdisciplinary modules along with group projects along with a PhD project giving me better insight into area of medical imaging. This course will enable me to pursue my research in this field of interest and act as stepping stone my further endeavours in academics and research.

Project: A pretargeted PET imaging strategy for nanomedicines: a theranostic tool

I completed an Integrated Masters degree in Forensic Chemistry at the University of Lincoln with a year in industry at GSK. During undergrad I completed a project focused on the synthesis and application of ferrocene sensors. Then in my fourth I worked at GSK as a Materials Scientist mostly using scanning electron microscopy, and I completed a method development project for testing the wettability of an API. I am excited to work within the CDT due to its interdisciplinary nature, as I will be able to build a wide range of skills in an area that I have a keen interest in.

I finished a Masters degree programme of Biomedical Engineering, specialising in Sensors and Signals at the University of Technology Vienna, after finishing my Bachelor’s degree in Electrical Engineering with specialisation in Power Engineering and Mechatronics at the University of Ljubljana.

During my Master’s course and internship at the United Nations Committee for the Effects of Atomic Radiation (UNSCEAR) I was drawn towards the field of medical imaging, which motivated me to write my master thesis about correlative imaging at Vienna Biocenter Core Facility.

I find the Centre for Doctoral Training in Medical Imaging a perfect fit for a young idealistic scientist who is passionate about ground breaking discoveries in a multidisciplinary working environment and making a difference by contributing to the quality of diagnostic approaches.

Project: A simultaneous multicontrast PET-MR sequence for comprehensive coronary plaque characterization

I completed my Integrated Masters degree in Biomedical Engineering at Imperial College London, during which I had the opportunity to contribute in a variety of design and research projects, such as making maps for visually impaired users, studying a fly’s neurological response to a visual stimulus and remotely identifying dangerous substances. I finally settled on studying medical imaging techniques. Among those, I am particularly interested in how to use optics to image the body.

The CDT in Smart Medical Imaging is an amazing opportunity to build the interdisciplinary skills found in the field of medical imaging, from biology to engineering. It is also the opportunity to meet like-minded people who share a passion in research and developing new techniques.

Project: DORMOUSE: Detection Of Reflected Microscopic Optical UltraSound Emission

I am an experienced musculoskeletal diagnostic & interventional consultant with a demonstrated history of working in the hospital & health care industry. I am skilled in spine, sports medicine, skeletal oncology, emergency medicine and have a particular interest in clinical governance, setting up national guidelines and strategy, multidisciplinary patient care pathways and healthcare quality improvement projects.I currently work as an Honorary Senior Clinical Lecturer at King’s College London, with a proven track record in academia, and continuous commitment to interdisciplinary translational research. I am a strong healthcare services professional and a graduate of both the Royal College of Radiologists and the Royal College of Surgeons.

I am a founding member of the Guy’s and St Thomas NHS Foundation Trust (GSTT) / King’s College London hip research team and imaging lead for GSTT Wrist and Hand services. Previously, I was an executive council member of the BSSR (2016-2019) and an executive committee member of the ESSR (June 2019-2021) and Clinical Governance, Audit & Quality Improvement Lead (2016-2021). I am a member of the:

-Royal College of Radiologists, UK
-Royal College of Surgeons, Edinburgh
-British Society of Skeletal Radiologists
-European Society of Skeletal Radiology
-British Association of Sport and Exercise Medicine
-International Society for Magnetic Resonance in Medicine

I am an active member of the London School of Clinical Radiology: London Deanery and an educational supervisor for undergraduate medical students and Radiology trainees.

Previously, I was an executive council member of the BSSR (2016-2019) and an executive committee member of the ESSR (June 2019-2021) and Clinical Governance, Audit & Quality Improvement Lead (2016-2021).

I come from the diverse city of Sarajevo in Bosnia and Herzegovina. In 2017 I started a masters in Medical Radiation Physics which brought about internships at the University of Sarajevo Clinical Center, and CERN. Previously I obtained an undergraduate degree in Physics and Electrical and Electronics Engineering from Middle East Technical University in Ankara, Turkey. I was part of ESRAP and EMBS research groups and the METU Tennis Team.
Throughout my short academic career I developed a strong interest in the emerging field of medical imaging – guided hadron therapy of cancer. I hope to grow into a scientist who will be able to profoundly contribute to the technological advances for bettering human health!

Project: A machine-learning approach to solving the SAR problem for ultrahigh field MRI

I graduated with a Masters degree in Chemistry from the University of Oxford. During the research year of this degree, I enjoyed working on a project developing a device with medical applications. The potential impact of this work inspired me to pursue research in medical engineering. I am currently interested in hyperspectral imaging (HSI) and the impact deep learning can have on medical technology. I am currently studying this in the Centre for Doctoral Training (CDT) in Surgical and Interventional Engineering.

After studying Physics for two years in the USA, I changed paths and started over at King’s College London where I graduated with a BEng in Biomedical Engineering in 2018. While working on my final year undergraduate project we developed an improved method for the creation of rib prostheses for lung cancer patients. During the course of the project I’ve grown increasingly interested in the field of bone reconstruction through the use of medical imaging and 3D printing, which inspired me to take up the challenge of a PhD.
I strongly believe that only through interdisciplinary approach and collaboration between scientists and clinicians can we progress in this cutting-edge research area.  A few years from now we should be able to use medical imaging for the diagnosis and treatment of cancer patients, such as producing bone implants, and meet their exact needs and improve their quality of life.

Project: Optimising repair of the thoracic wall following thoracic surgery

I graduated from Imperial College London in 2018 with a MEng (Hons) in Aeronautical Engineering. Following this I recently graduated from the University of St. Andrews with a Masters in Artificial Intelligence. During my Master’s degree I was particularly interesting in the field of deep learning applications in medical imaging which drove me towards my chosen masters thesis on breast cancer detection and segmentation using deep learning on mammograms. I am excited about the opportunities of completing a PhD in Medical Imaging as it creates a chance to generate ground breaking research in a multidisciplinary field whilst making a meaningful impact in the field of medical diagnosis. I particularly like the interdisciplinary nature of the CDT ranging from engineering to life sciences that enable candidates to develop a range of skills and techniques.

Project: General purpose abnormality detection in whole body PET

After graduating from UCL with a BSc in Physics with Medical Physics and being in full time employment in two different hospitals over couple of years, I was undecided whether to continue with my clinical career or pursue an academic one. So I decided to do the MSc Advanced Biomedical Imaging degree from UCL. For my research project I worked under Prof Jem Hebden, trying to detect a contrast agent with near infrared spectroscopy when injected intravenously. This is when I realised I would like to pursue a research career in biomedical science.
The MRC Biomedical Sciences DTP programme was ideal for me as it appreciated the diversity in students and I was made very welcome to work on a chemistry based project despite being from physics background. Through the alignment with Imaging CDT, I hope to broaden my knowledge of the ever-expanding field of medical imaging and utilise the multidisciplinary environment of both biomedical sciences DTP and imaging CDT to answer challenging research questions.

In 2019, I graduated with an MSc in Chemistry from King’s College London. During my masters project, I synthesised a novel δ-amino acid, a monomer for enzyme mimetic foldamers. I developed my interest in medicinal research during a summer placement at the University of Sydney, during which I investigated curcumin derivatives as potential inhibitors of the bacterial protein FtsZ using synthetic chemistry and molecular modelling. The CDT in Smart Medical Imaging is an opportunity for me to follow my passion and carry out impactful, multidisciplinary research in the medical field.

Project: Smart cell nuclear-localising 125/131I-labelled octreotates for sandwiched β- and Auger-particle therapy of metastatic neuroendocrine tumours

I graduated with a BSc in Robotics from the University of Reading in 2018. During my studies, I took an interest in medical robotics and imaging. After my undergraduate degree, I worked on post-stroke rehabilitation with the Biomedical Engineering team at the University of Reading. From there, I gained a Masters degree in Medical Robotics and Image Guided Intervention from the Hamlyn Centre, Imperial College London. My research interests include interventional robotics, particularly robotically driven catheter devices. I am currently studying robotic thrombectomy in the Centre for Doctoral Training in Surgical & Interventional Engineering.

I graduated from Imperial College London in 2020 with an MSci (Hons) degree in Chemistry. I completed my final year project under the supervision of Professor George Britovsek, researching oxygen insertion reactions using a novel palladium-methyl complex with a ‘boxmi’ ligand. It was during my final year that I began to learn about the field of molecular imaging too, and my interest in this area grew as I saw how chemistry, among many other disciplines, could be used to enhance people’s health and wellbeing. I will be working under the supervision of Professor Nicholas Long for my PhD and I am excited to develop my skills and learn much more about this evolving field.

Project: Multi-functional Metal-containing Probes for Brain Imaging

I graduated in 2018 from the University of Hull with an MChem in Chemistry. My final year project, under the supervision of Prof. Steve Archibald, focused on the pharmacokinetic modification of radiotracers. My passion for research in the development of PET tracers as medical imaging probes for diagnostic and therapeutic applications was established. I hope to further my understanding in this area of research and broaden my skills during my time at the CDT for medical imaging. I look forward to learning in a great environment full of support and peer collaboration.

I graduated from King’s College London in 2021, after the completing MEng Biomedical Engineer degree. I continued my professional career as a Research Assistant in the Department of Biomedical Engineering, where I gained valuable insight into the research environment. I am currently a PhD candidate in Surgical Robotics at the School of Biomedical Engineering & Imaging Sciences of King’s College London. My research interests include micro-surgical robotics for microsurgery, mechanical and electronics design, alongside systems modelling and control. In addition, I am a member of the Robotics and Vision in Medicine (RViM) Lab.

I graduated from the University of Oxford in 2020 with an integrated Masters in Physics. During this time, I developed an interest in particle accelerators, and pursued my MPhys project in laser wakefield acceleration in clustered plasmas with Marko Mayr in the Peter Norreys group. I was particularly drawn to particle accelerators used for medical applications due to the benefits that charged particle therapy can add to conventional radiotherapy. My interest in the latest technological advancements in healthcare led me to join the CDT in Surgical & Interventional Engineering, working with Steve Niederer in the Cardiac Electro-Mechanics Research Group (CEMRG). I am motivated by the translational research that the group conducts, and hope to contribute to this during my PhD.

I graduated from Cardiff University in 2021 with a MEng in Medical Engineering. As part of my degree I spent a Year in Industry during which I worked as a project engineer, and studied at Nanyang Technological University in Singapore for a semester. This experience, as well as a placement at St Thomas’ Hospital in London, gave rise to my interest in Medical Imaging.

As part of my degree, I have been involved in a wide range of engineering projects including a research project into the potential use of Computerised Tomography Fractional Flow Reserve (CT-FFR) as a replacement to traditional angiograms. For my Master’s project, I also completed a post-processing imaging project focused on assessing the impact of software specific imaging masks on quantitative medical image analysis.

My PhD at the Centre for Doctoral Training in Surgical & Interventional Engineering is focused on cardiac MRI.

I am a UCL Neuroimaging MRes graduate, interested in imaging of dementia and neurodegenerative disease in general. Over the next few years, I’ll be using quantitative MRI techniques to investigate and map iron and myelin profiles in patients with dementia.

Project: Translating brain magnetic resonance imaging signals to iron and myelin to appraise Alzheimer’s disease

In 2014 I graduated from St George’s University of London with a degree in Biomedical Science. Knowing I wanted to have a career in cancer research I completed an MSc in Immunology at King’s. During my MSc I was lucky enough to work with under Dr John Maher and completed a research project focusing on novel CAR T cells. I knew that I wanted to work more with CAR T cells and with these degrees I was able to get a job as a research associate at a biotech start up, Autolus. I worked there for almost 2 years before starting a MRes in Translational Medicine at Queen’s University Belfast in 2017. I managed to find my way back to King’s to start a PhD with the DTP researching a novel method to track CAR T-cells in vivo using both PET and fluorescence imaging.
During my time at the here I hope to further develop my knowledge of medical imaging, acquire new skills to equip me for a career in research.

Project: An indirect labelling approach to track the therapeutic CAR T-cells with dual PET and fluorescence imaging

After graduating with an Engineering degree from the Institute of Optics Graduate School in France, I came to England to pursue a Master of Biomedical Engineering at Imperial College London. After focused study of physics and optics, I wanted to apply my skills to the biomedical field; for me, a career in biomedical engineering would give more meaning to the work I do.

During my time at Imperial, I decided I wanted to specialise in medical imaging, a field which combines physics, optics and biomedicine. This CDT gives me the opportunity to use my full range of skills from my previous studies and my research interests in a PhD in Medical Imaging.

Project: High spatial and temporal resolution imaging of gut structure and microcirculation in response to nutrition intake and to therapeutics

In 2018, I graduated from Imperial College London with an MSci in Chemistry. During the final year of my undergraduate degree, I undertook a research project looking at the synthesis of tetrazine-based molecules for use as tracers in Positron Emission Tomography. I also studied the optional module of ‘Molecular Imaging’, during which I learnt about a variety of imaging techniques. The course and project fascinated me, and I decided to continue in the field of medical imaging.
I chose this CDT for the opportunity to work in close proximity with students from many specialties, and I hope to develop my insight into medical imaging whilst working to create a useful and unique radiometal based imaging tracer.

Project: New chelators for versatile coordination of PET, SPECT and radiotherapeutic isotopes

I completed an MSc in Mathematics split between Universitat de València and Universitat Politècnica de València. I then went on to do another MSc in Computational Mathematics at Universitat Jaume I, Castellón. I specialised in applied mathematics (mostly numerical methods and computer graphics) focused on simulation in Biomedicine.
I’m currently enrolled in an Innovative Training Network called PIC (Personalised In-silico Cardiology). My PhD project is on the optimisation of activation patterns during next generation CRT pacing. I hope that being in the CDT will be a great opportunity to develop my skills while learning new ones.

I graduated from Faculdade de Ciências da Universidade de Lisboa with a B.Sc. in Biomedical Engineering and Biophysics. During my bachelor I was involved in different projects related to medical imaging, namely my bachelor project which was related to MRI. Since I started studying MRI it became a very attractive subject to me for its complexity and because it involves knowledge of physics and different branches in mathematics, as statistics, signal processing and optimization, which I find very pleasant to learn more about and hope to do so during my PhD.

Project: High resolution imaging of tissue properties with optimized precision using Ultra High Field MRI

I studied data science gaining an MSc degree in Mathematics and Computer Science at the Skolkovo Institute of Science and Technology and another MSc degree in Applied Mathematics and Physics at Moscow Institute of Physics and Technology in 2019. My graduate project on medical image-to-image translation (MRI T1 – CT) using GANs was developed in collaboration with Philips Research and presented at various conferences. Thereafter, I continued working as a research scientist at Philips on AI-enabled radiology project dealing with uncertainty estimations in application to chest X-rays. My desire to pursue a PhD resulted from my experience and passion for AI-based solutions and computer science in general. Now, being a part of the CDT programme, I am excited to push the boundaries further contributing to the research project on the edge of machine learning and medical imaging.

Project: AI enabled motion corrected quantitative MRI of the fetal brain

I graduated from King’s College London in 2022 with a Bachelor’s degree in Neuroscience. During my final year research project, I became interested in brain imaging acquisition and analysis approaches. I had the opportunity to work under the supervision of Matthew Howard at the Centre for Neuroimaging Sciences on a project investigating the reliability of aberrant functional connectivity – assessed using fMRI – of the ventral tegmental area in chronic back pain patients. This, alongside my previous clinical experiences and a background in computer science, led me to decide to continue my studies at the CDT in Smart Medical Imaging. For this PhD, I wish to explore the unique properties of the Zero Echo-Time MRI sequence to accurately visualise cranial anatomy (bone, blood vessels, cranial nerves) that is otherwise difficult or impossible with conventional imaging.

Project: Development of Zero TE MRI to visualise cranial bones, nerves and vessels

In 2018, I graduated with a BSc in Mathematical Sciences from the National Autonomous University of Mexico. Shortly after I started an MSc in Mathematical Sciences at the same university. I graduated from my masters degree in 2020. Throughout this time I worked under the supervision of Dr Natalia Jonard in the field of topology. For my PhD, I decided I wanted to change the focus of my research and apply the mathematical knowledge I acquired during these years to make a more tangible contribution to society. This desire, alongside a new-found curiosity for artificial intelligence led me to decide to continue my studies at the Imaging CDT, where I will be working on a project to predict preterm birth from MRI using deep learning.

Project: Predicting premature birth from MRI using deep learning

I graduated with an MEng Mechatronic Engineering degree from the University of Manchester in 2020. I decided on the professional career I would like to pursue at a young age, after a patellar dislocation for which, due to surgical error, I had to be operated on several times. The incident inspired me to become a Medical Robotics researcher in order to help in the development of innovative solutions to precision surgical procedures. My research interest include the lack of tactile feedback in medical robotics systems and tools, which is a widely cited disadvantage associated with robotics. Currently, I am a PhD student trying to develop a novel technique to enable real-time force and shape sensing of an endoscopic tool called MorphGI.

In 2020, I completed an MEng in Engineering Science at the University of Oxford. My final project looked at the use of laser graphitisation to create structures within diamond, with a focus on creating structures that exhibit a desired interaction with light, such as waveguides. While this project was not strictly medical, I now plan to apply the imaging experience to a project in MRI at the CDT. In my spare time I enjoy playing a range of music across various instruments.

Project: Multiparametric diagnosis of fatty liver disease with magnetic resonance fingerprinting

I graduated with an MSc in Neuroimaging from the Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London (KCL) in 2016. For my MSc project, I studied correlations between functional magnetic resonance imaging (fMRI) and gene expression data, sparking my interest in deciphering the biological correlates underlying MRI data. Following my MSc, I joined the Perinatal Imaging and Health Department at St Thomas’ Hospital (KCL), where I used a histological approach to study an animal model of preterm brain injury. This research highlighted the need to identify MRI techniques that accurately visualise brain tissue damage non-invasively, for diagnosis and monitoring of disease.
The focus of my current PhD studentship (with Drs Po-Wah So and Maria Deprez) is to develop accurate MRI methods to image myelin, the insulator of our nerves, that is damaged in neurodegenerative diseases e.g., multiple sclerosis. I aim to identify a panel of quantitative MRI techniques which best predict myelin, using machine learning methods and corroborative histology and metal mapping alongside multimodal MRI.

I graduated with a BEng in Biomedical engineering from King’s College London in 2016. Throughout my degree, I was part of a few projects, one involved a novel and more efficient self-navigation technique for 2D ECG-free breath-held cardiac MRI and my 3rd year project was based on generating better 3D computer modelling of the heart using cardiac cine MRI. These all helped me to realise how much I enjoy being at the cutting edge of research and being able to create and incorporate novel idea in medical imaging, even more so during my year off to help care for my brother.
Therefore, when I discovered the project ‘The development of novel visualization techniques for medical images using a holographic volumetric display’ my inner science geek screamed and I had to be part of it. With this PhD, I will be able to achieve my goal as a researcher and inventor of medical technologies at a renowned university.

Project: Development of novel visualization techniques for medical images using a holographic volumetric display

I graduated in 2021 with an Integrated Master’s in Chemistry from the University of Bath. I did an industrial placement year at Pfizer as a synthetic organic chemist in chemical research and development. My Master’s project focussed on developing smart pH responsive chronic wound dressings and nanoparticles for pulmonary drug delivery. My PhD with the Torres/Surman groups aims to develop MPN gels as modular platforms for biomedical applications.

I have a Master’s in Biomedical Engineering from Aston University and won the Mechanical, Biomedical and Design (EPS) Departmental Prize for Outstanding progress.

In my master’s thesis, I developed a 3D model of the fluid flow of the aqueous humour in the eye to improve the understanding of ocular diseases. I have published two conference abstracts on this work; at BioMedEng21 in Sheffield and the South African Conference on Computational Mechanics 2021, held in Cape Town.

My research in the CDT consists of the assessment of fetal vascular ultrasound to identify growth restriction and reduce stillbirth. The objective would be to measure the fetal aortic elastic properties by using new signal and imaging processing techniques.

Project: Fetal vascular ultrasound assessment to identify growth restriction and reduce stillbirth

I graduated from the University of Bristol with an MSci in Chemistry with Industrial Experience. My final year research project focused on the synthesis of air stable tertiary phosphines employing an extended pi-conjugated backbone, which was carried out under the supervision of professor Paul Pringle.

The multidisciplinary CDT medical imaging programme hosted by King’s and Imperial provides an ideal environment where students are taught the skills and cross-disciplinary knowledge that prepares them for the pertinent PhD programme.

Project: Ultra-bright magnetic organic semiconductor nanoparticles for multimodal imaging

I obtained my bachelor’s and master‘s degree in Physics with a focus on Quantum Optics at the Friedrich-Alexander University of Erlangen-Nürnberg in Germany. In my master‘s project I had the chance to develop a magnetic field gradient correction method for non-Cartesian MRI in collaboration with Siemens Healthineers. MRI offers a versatile field of research by which I am fascinated since high school. By joining the CDT, I want to broaden and deepen my knowledge in this field, to make a contribution and most importantly to connect with fellow students and researchers.

Project: High resolution optimal precision quantitative MRI at Ultrahigh Field

I graduated with a BSc (w/ Hons) in Chemistry with Medicinal Chemistry from the University of Glasgow in 2015, where I spent a year investigating the use of transition metal-based radiopharmaceuticals for diagnostic imaging; with a focus on positron emitting nuclei. Following so, I undertook a MSc in Medicinal Chemistry at the University of Copenhagen, in which I spent my project year investigating the development of PET tracers for the selective imaging of serotonin-7 receptors.
I look forward to working in the interdisciplinary CDT, focusing on the development of stoichiometric radiolabelling with carbon-11 with the use of microfluidic reactors.

Project: Nanoscale microfluidic reactions: near-stoichiometric™ radiolabeling for PET

My journey at the Medical Imaging CDT has so far been wonderful. In 2017, I graduated from Imperial College London with an MSci degree in Physics.  My research involves using deep learning techniques to tackle compressed sensing for extremely undersampled dynamic MRI. My current research interests include (but not limited to) Bayesian Deep Learning and Generative Models. I’m supervised by Professor Daniel Rueckert from Imperial College and Professor Jo Hajnal from King’s College London. I also enjoying playing tennis and I’m a keen climber!

Papers and publications will appear here soon (hopefully):
https://scholar.google.co.uk/citations?user=AKsfdDwAAAAJ

Project: Learning optimal image representations for MRI reconstruction, synthesis and analysis

I graduated in 2022 with an Honours BEng Degree in Biomedical Engineering at King’s College London where I had the opportunity to enhance my knowledge to solve impactful healthcare problems with cutting-edge technology. During my undergraduate studies, I worked on several projects ranging from assistive devices designed to aid disabled people to artificial intelligence algorithms involving heart arrhythmias. In my 2nd year I have been granted the King’s Undergraduate Research Fellowship (KURF) to further develop an AI algorithm which, based on imaging, predicts the success of Catheter Ablation (CA) therapy for atrial fibrillation, which mainly became my area of interest. I strongly believe that my PhD project will lead to novel breakthroughs in the field of cardiovascular diseases, and the integration of Reinforcement Learning algorithms would bring a major benefit to our end-user, the patient.

Project: Application of Deep Reinforcement Learning to Predict Ablation Therapy for Atrial Fibrillation from Imaging Data

I finished my Bachelor’s studies in Electrical and Electronic Engineering at the University of Liverpool in 2018 and received a Master’s degree in Computer Science from UCL in 2019, where my course focused on image analysis, computer vision and machine learning. I was supervised by Prof. Daniel Alexander and Prof. Pearse Keane and developed a reinforcement learning algorithm, which optimised the treatment intervals of age-related macular degeneration. After graduation, I joined the UCL Institute of Ophthalmology and Moorfields Eye Hospital as data scientist and research assistant. During that period, I created different AI algorithms for assisting the diagnosis and prognosis of medical retinal diseases for the world-leading eye hospital. My algorithm was published and integrated into the cloud-based hospital setting. As part of this experience, I developed a deeper interest in the field of AI-assisted interventions for retinal images.
I am now part of the RViM group and a PhD candidate, co-supervised by Prof. Timothy Jackson and Dr Christos Bergeles. I aim to solve retinal imaging problems for diabetic retinopathy with a team of clinicians and engineers.

I studied Chemistry with Molecular Physics at Imperial College London with my final project under supervision of Dr James Wilton-Ely focusing on sustainability of palladium cross-coupling reactions. After being exposed to the importance of chemistry in medical imaging and to the group’s work applicable to healthcare, I wanted to use my skills for a project exploring immunotherapy options by connecting CO to gene expression in different types of cancer.

Project: Enabling immunotherapy through the detection and sequestration of CO by fluorogenic probes

I first studied mathematics, physics and chemistry at Lycée Stanislas in Classes Préparatoires in Paris. After the competitive examinations I joined Telecom ParisTech in 2015, an engineering school specialized in Mathematics and Computer Science. I studied statistics, optimization and Machine Learning. After two years, I decided to take a gap year to work at BioSerenity’s research lab, a start-up creating devices for epileptic seizures detection. I was in a shared laboratory with The Brain and Spine Institute at Hôpital de la Pitié-Salpêtrière in Paris. Eventually, I joined the University of Amsterdam in 2018 for a MSc in Big Data as part of an exchange program with my school.

Project: Synergistic joint variational neural networks for PET-MR image reconstruction with generative modelling priors

I graduated with a MEng in Electrical and Computer Engineering from the University of Patras, Greece, in 2019. My dissertation focused on Medical Simulation for Surgery training and planning in Human Respiratory System. I did an internship at Surgical Robot Vision Research Group of University College London (UCL) and worked on 3D Ultrasound Reconstruction of malignant masses in kidney combining robotics and computer vision applications.
I am currently a PhD student in the Centre for Doctoral Training (CDT) in Surgical & Interventional Engineering and work on augmenting the capabilities of iOCT imaging through incorporation of real-time AI in the acquisition and processing pathways towards the creation of a robust navigation system that guides therapy implantation in vitreoretinal surgery.

I completed my BEng in Biomedical Engineering at King’s College London. During those years, I developed a fond interest in the computational side of the course, which I further explored with my project in the application of artificial intelligence for the automated detection of incidental extra-cardiac findings in cardiac MRI scans. After that, I pursued my interest in the area with my MSc in Medical Robotics and Artificial Intelligence at UCL. As part of this course I completed a project that aimed to diagnose necrotising enterocolitis, which is a high morbidity disease that affects premature infants, from abdominal X-rays. The CDT in Smart Medical Imaging offers the perfect opportunity to consolidate my skills in the area and further deepen my knowledge of the subject, in a lively and stimulating environment.

Project: Synergistic image analysis of longitudinal cardiac MRI

Motivated by my passion of technology and healthcare, I earned an MSc in Biomedical Engineering and Biophysics from the University of Lisbon, in 2021. I then worked as a Research Assistant at King’s College London, where I built deep learning methods for anomaly detection in brain PET-MR epilepsy data and age-prediction models in neonates to study neurodevelopment. My time at King’s led me to pursue a PhD with the CDT in Smart Medical Imaging, where I will apply my experience in deep learning to explore the early fetal brain development and certainly grow, as a researcher and person, throughout the process.

Project: Exploring early fetal brain development: a deep learning approach

After studying theoretical Mathematics and Physics, I pursued an engineering degree in computing at Télécom Paris in France, where I obtained an MEng in Cybersecurity in 2018. Being already interested in Machine Learning for a long time, I decided to change path and go for a double degree to study at Imperial College London, where I graduated from an MSc in Machine Learning in 2019. There, I had the opportunity to quickly apply ML to Medical Imaging. Especially, I studied classification problems of MRI brain scans for Alzheimer’s disease diagnosis and prognosis for my master thesis, under the supervision of Dr Elsa Angelini. This project ended with a publication at the 2020 ISBI conference. This wonderful experience really reinforced my taste for research, and especially in the field of medical imaging, where using ML has definitely a strong positive impact on people’s lives. Even if I was eager to go into research, I decided to take a 1-year break to work as a data scientist. While this experience has broaden my view and understanding of concret challenges, it has also strengthen my desire to pursue a career in research. Going for the CDT program was really the choice of excellence in that sense, given the interdisciplinary and state-of-the-art work which is conducted there. I will be studying the use of ML strategies for quantification of strain and motion in cardiac MRI scans.

Project: Machine Learning for Automated Heart Strain and Motion from DENSE

My research experience started during my undergraduate studies as a Research Intern focusing on computational chemistry and an internship (3 months) in nanobiotechnology at a different institute. I followed this with my Master’s project (24 months) in organic chemistry focusing on the development of new metal-catalysed synthetic routes. In order to extend my knowledge in this area, I secured a Research Internship at ETH Zürich in Switzerland (8 months), working on metal-based catalysis.
I now wish to apply my knowledge of metal-based chemistry to medical research, in particular imaging and therapy. With this in mind, I started work 3 months ago on multifunctional MRI contrast agents.at the Institute of Biomedical Engineering at KNU. This will provide excellent preparation for the proposed project with Dr Wilton-Ely at Imperial College, addressing the combined use of imaging and therapy. Throughout these experiences, I have gained skills in synthesis, solution and solid-state characterisation, experimental design and computational modelling to help me achieve more in my research and address society’s healthcare challenges.

I graduated from King’s College London in 2022 with a BEng (Hons) in Biomedical Engineering. During the summer of my second year, I was fortunate to participate in a research project with Dr. Ernest Kamavuako investigating the variability of machine learning for prosthetic control. This sparked my interest in AI. After that, I undertook a research project with Dr. Sebastien Roujol in my final year, developing a deep learning programme that can reduce motion artefacts in cardiovascular magnetic resonance imaging (CMR).

The EPSRC CDT in Smart Medical Imaging interested me as it offered me the chance to push my boundaries and participate in an interdisciplinary project that would allow me to further develop my skills in AI and medical imaging. I look forward to gaining experience working on state-of-the-art research in my PhD which focuses on AI-enabled assessment of cardiac function from echocardiography.

Project: AI-Enabled Assessment of Cardiac Function from Echocardiography

In 2016 I graduated from Lisbon School of Health Technology in Portugal with a BSc in Nuclear Medicine. Throughout my undergraduate studies, I had the opportunity to learn different areas of Nuclear Medicine, such as Radiopharmacy, Medical Physics and Radiobiology.
After my graduation I worked as Nuclear Medicine Technologist at Barts Health NHS Trust where I improved my skills in SPECT/CT, PET/CT and Radiopharmacy.
In 2017 I undertook an MSc in Radiopharmaceutics and PET Radiochemistry at King’s College where I undertook a research project on the assessment of the potential of 67Ga-DOTA-PSMA for metastatic-castration resistant prostate cancer.
The CDT program is going to give me the opportunity to combine not only my interest in Nuclear Medicine and research, but also to show people that radiation can be successfully harnessed to benefit Medicine in a multitude of ways.

Project: How do medical imaging radioisotopes used for diagnostic imaging and cell tracking affect cancer and immune cells?

Originally from Greece, I studied for a double Bachelor in Electronics Engineering & Computer Science and Education. After my internship in the R&D department of Intracom Defense Electronics (where I met inspirational people and stayed for 3 more years), I was part of a team at the University of Athens Media Labs where we designed and developed an educational video game for children with mild learning disabilities. Exploring myself and my interests, I took a few gap year(s), travelling and living in Austria, the Netherlands, Norway and the UK. Here, I worked for a tech startup creating an in-house Linux based Operating System and a magic ‘Harry Potter’ Wand, used to teach children how to code. Before returning to academia after 9 years, I helped develop the pipeline in a creative production studio, specialised in VFX and animation. It is my honour to receive my scientific training at King’s College London and especially in such an exciting topic! I believe that every human should have easy access to high-quality healthcare and I hope that I will be able through the time to grow as a scientist and be able to contribute in this field.

Project: Predicting autism spectrum phenotypes from neonatal brain connectivity

I currently hold Masters diplomas in both Computer Science and Medical Imaging. I am very passionate about both fields and I have always wanted to pursue a research career in a multidisciplinary environment. At King's I found the perfect mesh between these two worlds and a great environment for learning, with support from the academic community. My project focuses on novel imaging biomarkers for prognosis of developmental outcomes in babies born preterm.

Project: Novel imaging biomarkers for prognosis of developmental outcomes in babies born preterm using machine-learning

I am a graduate from the University of Birmingham with an MSci in Chemistry with Industrial Experience. During my industry year, I worked in the R&D department of a global plastic films company, DuPont Teijin Films, developing flame retardant and laser engravable overlay films. For my master’s year, I investigated the photophysical properties of luminescent iridium(III) probes labelled on gold nanoparticles for bioimaging applications, under the supervision of Prof. Zoe Pikramenou. I developed a keen interest in tracer compounds, medical imaging and the substantial theranostic applications of this research area. I am excited to pursue this further at the CDT working under Prof. Mark Green, researching luminescent/PET active indium phosphide quantum dots for multimodal imaging of prostate cancer.

Project: Luminescent/PET-active quantum dots for multimodal imaging of prostate cancer

In 2021, I graduated from King’s College London with a First-Class MSci in Chemistry with Biomedicine. In my time as King’s, I was also involved on the committee of multiple societies; for example, I was the President of the Chemistry Society and Vice President of the Men’s Football Club. My masters year involved a project with Dr Graeme Hogarth developing bifunctional dithiocarbamate chelators for radiopharmaceutical applications. Through my project, I developed an interest in the synthesis and applications of smart imaging probes, leading to my project of Dual labelled phase change nanodroplets for ultrasound guided drug therapies under the supervision of Dr Maya Thanou and Prof Mark Green.

Project: Dual labelled phase change nanodroplets for ultrasound guided drug therapies

I completed my undergraduate degree in Mechanical Engineering as part of the 2+2 programme between Wuhan University of Technology and the University of Birmingham and entered Imperial College London to pursue an MRes in Medical Device Design and Entrepreneurship afterwards. With both medical device R&D and business expertise on technology conversions, I am now working in the photonic and ultrasonic research group directed by Dr Wenfeng Xia at Kings College London.

I am currently undertaking a PhD in Image Sciences and Biomedical Engineering where I am working on Simultaneous Localisation And Mapping (SLAM) algorithms together with Machine Learning for the use in miniature steerable chip-on-tip endoscopy used in eye surgery. I have a background in electronics and embedded systems design and have worked for 5 years in different sectors including energy, defense, infrastructure, consumer goods and electronic product development .
In 2013 I graduated from Lancaster University with a First class MEng degree in Mechatronics Engineering. During my time there I worked on the control of a nuclear decommissioning robotic manipulator and the development of an instrumented landmine detector using speech recognition algorithms.
My research interests include robotics, computer vision and Machine Learning and their use in medical aplications.

 

Project: Deformable 3D reconstruction of endoluminal anatomy by miniature steerable chip-on-tip endoscopy

I graduated in 2018 from the University of Exeter with first-class honours in MSci Natural Sciences. Within my degree, I enjoyed studying the physics that underpins biological and medical processes and tailored my modules choices to reflect this. Undertaking my master’s project in imaging Alzheimer’s disease tissue using spectroscopic techniques showed me how improving diagnostics can have a positive impact on patients’ lives.
The CDT programme will allow me to further improve my medical imaging knowledge and continue using interdisciplinary approaches to help improve diagnostic tools, whilst providing me with a strong foundation to carry out scientific research.

Project: Multiparametric low-dose PET-MR for single-scan diagnostic imaging of memory clinic patients

I graduated with an MChem in Chemistry from Durham University in 2017 where I completed my Master’s project under the supervision of Dr James Walton. My research project involved the synthesis of ruthenium based anticancer agents, focusing on the photoactivation of histone deacetylase inhibitors. Using coordination chemistry and understanding how it can be applied to the synthesis of cancer therapeutics motivated me to pursue further research into this field. 
My PhD project involves the synthesis and analysis of chelators radiolabelled with 213Bi and 225Ac as radionuclide therapies for prostate cancer. I am excited to expand my knowledge in this area and to embark upon a project which combines radiochemistry and organic synthesis in the development of novel prostate cancer therapeutics.

I graduated with a Bachelor’s degree from Northeastern University (CN) in 2018 and received my Master’s degree from Shanghai Jiao Tong University in 2021. My Master’s projects involved medical image analysis for multi-modality data, such as brain MRI and chest CT. In 2020, my teammates and I developed an intelligent algorithm that can precisely differentiate COVID-19 from community-acquired pneumonia.

Currently, I am a PhD student co-supervised by Dr Rachel Sparks and Prof Sebastien Ourselin. My research interests include few-shot learning and robust machine learning in computer-aided surgical intervention. Besides, my research project mainly focuses the laser interstitial thermal therapy in minimally invasive neurosurgery, which aims to predict accurate treatment volume and develop surgical planning based on medical imaging and artificial intelligence.

In 2020 I graduated from Peking University with an MSc degree in Biomedical Engineering. In my graduate project with Dai group, I worked with “Enhanced Bioluminescence Imaging of Inflammation Based on Dual-color Nanobubbles”. My current research interests lie primarily in nanomedicine, molecular imaging and translational research. And CDT is highly interested in translational research. In CDT I can find the most supportive environment. In the future, I will strive to participate in translational medicine. With necessary techniques and skills obtained as a PhD student, I will be able to fulfil my personal goals.

Project: Integrating imaging and drug delivery systems to improve radiotherapy

I received my BEng degree in Electrical Engineering from Xi’an Jiaotong-Liverpool University in 2019, followed by my MRes degree focused on bioengineering at Imperial College London in 2020. Before I joined King’s College London, I worked as a research assistant at Shenzhen Technology University. I investigated cardiovascular health and machine learning algorithms. I will continue my research on cardiovascular simulation models, arterial health and data-driven models in my PhD project.

My name is Joana and I am very passionate about research. In 2014, I obtained a BSc in Nuclear Medicine at Lisbon School of Health Technology, Portugal, followed by five years of working experience as a Nuclear Medicine and PET/CT technologist across several NHS hospitals in UK. During the 5-year work experience, I began my research interest in the clinical environment in which I had the opportunity to improve the everyday practice of Conventional Nuclear Medicine, PET/CT and Radionuclide Therapy. This inspired me to take up the challenge of an MSc in Radiopharmaceutics & PET from King’s College London in 2019 to further increase my knowledge and work towards a research career. My MSc research project involved PET imaging with carbon-11 radiolabeled endogenous compounds under the supervision of Dr. Salvatore Bongarzone, Dr. Antonio Shegani and Prof. Toni Gee. This has not only immersed me in a network of researchers across many fields, but it has also sparked my interest in continuing exploring new areas. The CDT is an exciting opportunity to play the strengths I already have from my work and MSc experience, and to begin to appreciate the complexity of radiochemistry before it is implemented into clinical studies, valuing the opportunity to work together with world-class experts in the field. I am excited to expand my knowledge in the field of radiochemistry and to make the most of the resources available in the CDT’s multidisciplinary team at King’s.

Project: One-step, site-specific labelling of His-tagged proteins with technetium-99m and rhenium-188 for cancer imaging and therapy

In 2016 I was awarded with a B.Sc. in Molecular Genetics at King’s College London, with a year abroad at the University of Melbourne. During my undergraduate course I was particularly interested in cancer genetics and immunology and have undertaken a few short research projects in cancer biology. Currently, I am a 2nd year student on the MRC Doctoral Training Programme. Last year I have completed 3 rotation projects in different laboratories across King’s College campuses, which gave me a chance to get insight into very diverse research fields, learn a range of new skills and eventually develop a strong interest in molecular imaging.
My PhD project will focus on the in vivo trafficking of essential trace metals in health and disease using PET imaging. It connects basic biology research with a translational approach, where the development of imaging tools detecting the distorted metal homeostasis in vivo could be used for the diagnosis, monitoring and predicting therapy outcomes in cancer (altered copper homeostasis) or diabetes (altered zinc homeostasis).
 

In 2021, I graduated from Cardiff University with a MEng in Medical Engineering. During my masters project, I completed a project finding optimal methods of segmenting glioblastoma tumours. This began an interest in medical imaging, which I have been able to combine with my interest in obstetrics for my PhD.
The focus of my PhD, under the supervision of Dr Andrew Melbourne, is measuring placental function in fetal growth mostly using MRI data.

I am a Biomedical Engineer from Portugal. I completed my undergraduate and Masters studies in the Faculty of Sciences of the University of Lisbon, with two internships abroad: one in Oxford and one in Berlin for my bachelor and master projects respectively. Then I worked for approximately four years in Berlin in the German Heart Center Berlin and Charité Centre.
My research has focused on cardiovascular image processing, together with some modelling. Topics include blood pressure, blood kinetic energy, heart energetics, biomechanical heart modelling parameterization.

I graduated from Imperial College London in 2017 with an MEng in Aeronautical Engineering. Though medical imaging seems as though it would be unrelated, I will be taking forward my experience in computational fluid dynamics to understand blood flow in the coronary arteries.
I think that the CDT will be an ideal way to re-specialise due to its interdisciplinary environment and I hope to get a broad understanding for this field, adding a new dimension to the work I would have been doing otherwise.

Project: Real-time assessment of coronary haemodynamics via hybrid fluid dynamics & machine learning approach

I completed my high school education in Galway, Ireland, before studying physics at the University of Edinburgh where my masters thesis focused on an experimental project investigating new types of PET imaging. After completing my degree I moved to the Netherlands where I worked with a company developing organic electronics.
During my doctoral training I hope to develop a deep understanding of photoacoustic ultrasound, alongside gaining knowledge and experience in the field of medical imaging as a whole. Specifically I am excited about working towards the development of new types of medical imaging which will be of direct and tangible benefit to society

Project: Photoacoustics and ultrasound computed tomography

I received my Master’s degree in physics from Indian Institute of Technology, Delhi, India, before which I had finished my bachelor’s in physics from Hansraj College, University of Delhi. It was during my master’s thesis at IIT that my interest began to develop in biomedical imaging and the potency it holds towards machine learning algorithms. Post my master’s degree, I shifted gears a little and decided to work in a computational neuroscience lab at NCBS, Bangalore. There I gained a better understanding of how learning and memory persists in the brain with the help of modeling algorithms. While working at NCBS, I realized that I wanted the best of both worlds and applied for this PhD in brain imaging at KCL. After having spent a hefty chunk of time studying classroom physics, I’m really excited to be getting this kind of a hands-on knowledge and experience in biomedical sciences at the CDT.

Project: Resolving the cortex with ultra-high resolution MRI to detect epileptic lesions

I have graduated with a Master’s degree in Pharmaceutical Chemistry with a Year in Industry from the University of Leicester in 2020. For my industrial project, I had the unique opportunity to work for AGFA, Belgium; here I worked on formulations of new flexible UV-based inks. My Master’s thesis under the supervision of Prof. Piletsky was based on the development of nanomolecularly imprinted polymers (nanoMIPs) to selectively target epitopes of the enzyme G6PD and measure the effect onenzyme activity. I am now an aspiring PhD student at King’s, where my project is focusing on the development of quantum dot nanoparticles for the potential application of image guided surgery of glioblastoma. For me, this project aligns with my strengths and sets out ambitious goals to revolutionise medical imaging. Furthermore, working as part of the Doctoral Training Programme is an exciting opportunity to grow individually, as well as collaborate with fellow academics, which I am personally looking forward to.

During my MEng in Electronics and Information Science at the University of Cambridge, I developed an interest in applying my technical expertise to problems in healthcare, with a thesis project to develop the next generation of smart digital stethoscopes.

I went on to work as an Embedded Engineer at a world-class surgical robotics company, before joining a specialist AI consultancy where I worked on a broad range of projects (from developing a solution to tackle bias in Machine Learning, to conducting basic research in physics-driven reinforcement learning).

I am very excited to once again work within the field of Biomedical Engineering, applying my skills in Machine Learning to develop novel approaches to pancreatic image analysis within the BioMedIA group.

Project: Synergistic Representation Learning for Pancreatic Image Analysis

In 2020, I graduated with an MSc in Biomedical Engineering from the University of Strathclyde, having previously completed a Physics degree at the University of Edinburgh. I developed an interest in the medical applications of physics during my undergraduate degree, specifically MRI. My PhD project is within the MR physics group at King’s, under the supervision of Dr Ozlem Ipek and Prof. Jo Hajnal and focuses on developing a novel RF-coil-array to enable safe and high-quality imaging of adults and children with implanted neurostimulation devices.

During my Physics studies at the University of Bath, I was drawn particularly to Medical Physics, especially Magnetic Resonance Imaging (MRI). The fascinating idea of using machine learning in speeding up MRI acquisition and post-processing inspired me to study for a Master’s degree in Applied Computational Science and Engineering at Imperial College London. In this venture, I worked in collaboration with NASA to develop a machine learning-based tool to detect fracture types on Jupiter’s moon, Europa. It allowed me to substantiate my coding skills and begin working on machine learning.

The EPSRC CDT in Smart Medical Imaging has now provided me with an exciting opportunity to start my next adventure. I am looking forward to contributing to the research using machine learning to speed up the data acquisition processes for Cardiac MRI and to utilise the power of digital data in better understanding diseases.

Project: AI enabled 3-fold accelerated in vivo Whole-Heart Diffusion Tensor Cardiac MR

I obtained my undergraduate degree from the University of York where I studied Molecular Cell Biology. During my studies, I undertook a placement year at AstraZeneca, where I was conducting high-throughput compound screening and profiling experiments for dose-response studies. I completed my dissertation project in Dr MacDonald’s lab exploring cell surface recycling pathways in yeast. Through the PhD programme within the King’s BHF Centre of Research Excellence, I aim to gain expertise in the mechanistic origins of heart disease. What fascinates me about the programme is that it allows for greater specialisation in the therapeutic applications of molecular MRI tools.

I have previously studied mathematics, first gaining a BSc Mathematics from St. Andrews University and later an MSc from Oxford University in Mathematics and Theoretical Computer Science. I also had the opportunity to study abroad at University of Toronto and complete a research internship in Vienna during this period.

I have since spent several years working as a data scientist in industry, with the last two years as part of an AI team specialising in Natural Language Processing (NLP). Learning about the many incredible applications of deep learning in the healthcare field has inspired me to join the Smart Medical Imaging CDT. I am excited to develop my knowledge of medical imaging and have the opportunity to contribute to deep learning research in such a worthwhile field.

Project: Mining for iron in the brain: a deep learning approach

I graduated from the University of Leicester in 2017 with a BSc (Hons) in Biological sciences. Following this I enrolled at University College London as part of the Msc in Advanced Biomedical Imaging. During this course I completed a project in developing an MRI protocol to quantify the T1 of perivascular fluid compartments within the brain as a novel biomarker of glymphatic function.
I am excited to expand my knowledge in the field of bioengineering and further my research skills in the CDT’s multidisciplinary team at King’s.

Project: Imaging cancer response and resistance to therapy using the chick CAM and isolated perfused tumour

I graduated with a BSc in Biomedical Engineering in 2016 from Imam Abdulrahman bin Faisal University. A few months later, I was offered an academic position at the same university, where I participated in research studies and assisted with teaching.
I received a scholarship from my employer to study MSc in Biomedical Engineering at the University of Bristol. My project focused on improving the homogeneity of the magnetic field in MRI machines.

Project: Machine learning for improved clinical decision making ahead of epilepsy surgery

After obtaining my undergraduate degree in Mechanical Engineering from the American University in Cairo, Egypt in 2017, I went on to pursue a Master’s Degree in Biomechanical Engineering at the Ecole Polytechnique in Paris, France. I then worked for a year at CorWave, a medical device design startup, designing and simulating left ventricular assist devices. I am currently working at the Aswan Heart Centre (AHC) in Aswan, Egypt and starting my PhD project at King’s College London, in collaboration with AHC, tackling the disease of pulmonary hypertension. The project will aim at modelling the disease and using simulation for personalised treatment planning, using patient cohorts from AHC.

I graduated in 2021 with a BEng (Hons) in Biomedical Engineering from King’s College London. After graduating, I pursued the MSc in Healthcare Technologies at King’s College London, with a focus on AI and medical image computing. During my studies, I was involved in various research projects, including investigating neurodevelopmental outcomes in preterm-born individuals and developing deep learning algorithms for fetal neuroimaging segmentation tasks. During the final year of my BEng, I was fortunate to undertake an inter-disciplinary research project using machine learning to evaluate left ventricular outflow tract obstruction in hypertrophic cardiomyopathy under supervision of Professor Alistair Young and Professor Pablo Lamata. During this project, I developed a keen interest in AI-enabled imaging and computational modelling for enhancing the understanding of prevalent cardiac disorders and consequently decided to pursue a PhD in the CDT in Smart Medical Imaging to build upon my research interests. I am excited for the opportunity to collaborate with Dr Martin Bishop and Philips Healthcare Research during my PhD to improve ablation target guidance for patients with cardiac arrhythmias using a combination of AI and cardiac modelling.

Project: Intra-procedural updating of cardiac digital-twins for automated arrhythmia ablation target guidance using novel electroanatomical system

I graduated from the Aristotle University of Thessaloniki with a diploma (equivalent to MEng) in Electrical and Computer Engineering. I have always had a keen interest in human brain research and how data science and machine learning can be leveraged to address biomedical engineering challenges. In my master thesis, I had the chance to work on advanced signal processing and machine learning techniques applied to medical data.
During my time in the CDT, I hope to further my knowledge in deep learning, collaborate with people from various disciplines and contribute to the exciting research field of medical imaging.

Project: Development of a decision support tool for neuroimaging using explainable ML

In 2019, I completed my Integrated Masters degree in Biomedical Engineering and Biophysics from the University of Lisbon, Portugal. I had the opportunity to conduct my thesis project at the University of Cambridge, where I developed a project on the use of deep learning to create synthetic CT images. My passion for deep learning in medical imaging and neuroscience led me to pursue a PhD with the CDT in Smart Medical Imaging. I will be investigating the use of interpretable deep learning in order to predict cognitive development from brain MRI data with meaningful explanations.

Project: Building sensitive models of cognition using interpretable Deep Learning

I have completed my Bachelors and MEng in Biomedical Engineering at Kings’ College London. During these years, my interest for computational modelling and AI grew significantly. I have had the opportunity to work for some great research studies in the area of cardiovascular diseases which lead me to undertake this new project on Deep Learning for cardiac MRI. I am very grateful to King’s for providing me with the opportunity to grow so much and to really empower my passion. I hope the CDT will give me even more skills and leverage to be able to develop new ideas and to solve complex physical and medical problems through which I could contribute to the wellbeing of humanity.

Project: Automated 4D function of the heart

I am a PhD student in Surgical and Interventional Engineering supervised by Prof Sebastien Ourselin, Prof Prokar Dasgupta, and Steven Bishop – Head of Research and Strategy at CMR Surgical. My work focuses on surgical phase recognition from robot-assisted radical prostatectomy procedures with data recorded from the DaVinci and Versius robots. The objective is to understand the surgical workflow, enhance team training and improve clinically relevant outcomes.
In 2020, I obtained an MSc degree in Computer Vision, Robotics, and Machine Learning from the University of Surrey. My Master’s project centred on using convolutional neural networks to predict malignancy in breast cancer. In 2019, I received an MSc in Data Science and Advanced Analytics from the University NOVA of Lisbon. This led me to work as a Deep Learning Engineer in medical imaging at Radiomics based in Belgium. I then decided to return to the UK to specialise in Surgical Data Science at King’s College London.

I recently graduated from Imperial College London where I was awarded a Masters in Bioengineering. My research project at Imperial focused on deciphering the role of MicroRNAs on gene regulation. I was able to develop and utilize novel bioinformatic prediction tools to aid in eliciting the extent to which microRNAs contribute to the progression of atherosclerosis through their impact on gene regulation.
I chose the CDT program as it provides a unique opportunity to work within a clinical environment where interdisciplinary collaborations and the development of industry skills are encouraged. My major research projects to date have been associated with Cardiovascular disease, I look forward to advancing my knowledge in the application of imaging techniques in order to provide clinical solutions to cardiac pathologies.

Project: Molecular imaging tools to identify evolving cardiac injury caused by cancer therapy

I received my undergraduate degree in Telecommunication Engineering from the University of Liverpool in 2020, followed by a Master’s degree focused on medical images and artificial intelligence at Imperial College London in 2021. At the CDT, I am working with Professor Tom Vercauteren on medical image computing. My research areas of interest include medical image computing, artificial intelligence, machine learning and computer vision.

Project: Semi-supervised detection and tracking of instruments for robotic surgery guidance

I completed my Bachelor’s degree at the Nanjing University of Science and Technology in China in 2019 and then chose to study for a Master’s degree in Communications and Signal Processing at Imperial College London. During this one-year programme, I found my interests in medical imaging using state-of-art optical technologies and their clinical applications and after graduation, decided to conduct relevant research at King’s in 2020. Currently, my research interests focus on biomedical imaging modalities, especially photoacoustic imaging. I am working on a project about multispectral photoacoustic imaging with affordable light sources, which aims to improve the accuracy for oxygenation measurements in blood vessels and the maximum imaging depth using machine learning tools. Hopefully, it will be applied to help the clinical diagnosis of Necrotizing Enterocolitis (NEC) in the neonatal intensive care unit.

I graduated with a Biomedical Engineering Degree from Carlos III University of Madrid in 2019. During my third-year summer break, I had an internship at the Biocruces Bizkaia research lab in Barakaldo. I worked in conjunction with Neuropsychology and Computational Neuroimaging in several projects regarding Alzheimer and autism diseases using functional and structural MRI images. I hold a Masters degree in Healthcare Technology from the King’s College London. My research areas of interest are medical robotics and artificial intelligence. I am currently working on integrating haptic and visual data for low latency transmission.

I have graduated with a bachelors degree in Mathematics and have completed my master’s degree in AI & Data Science. During my master’s degree, I completed a project using deep learning techniques to quantify the grade of reticulum fibrosis as well as to determine the morphological features of the fibers themselves. From my previous experiences I have really enjoyed applying my mathematical knowledge as well as computer programming skills to medical datasets which is why I have chosen to do a PhD. My PhD project is on “Modelling the Circulation of the Eye for Organ Preservation Device.”

I currently hold a Masters degree in Biomedical Engineering from King’s College London. During my time at King’s, I grew a significant interest in cardiac MRI which was rooted in my existing passion for the fields of cardiology, computer science and physics. For my third and fourth year, I had the opportunity to work on two deep learning projects in adult and foetal cardiac MRI respectively. In these projects, I developed a novel approach for fully automated detection of the quiescent phases of the cardiac cycle from CINE images and a fully automated image segmentation model for 3D motion-corrected foetal heart scans.

I was also actively involved in the field by taking up a software development internship with Cydar Medical Ltd. Learning and experiencing first-hand the positive impact that medical imaging and healthcare technologies have has inspired me to pursue a PhD in the field. For my PhD, I will continue to work in the cardiac MRI field which I am passionate about and get to know and work with other inspiring researchers.

In 2020, I graduated from the University of Warwick with an MChem degree in Chemistry with Medicinal Chemistry. For my final year master’s project, I worked on the synthesis of novel osmium(II) anticancer complexes with the Sadler group, focusing on their abilities to manipulate redox chemistry in vivo and determining their mechanism of action. During my third year, I undertook an international placement at Monash University, Melbourne working with the Paterson group on the synthesis of a 68Ga bifunctional chelator for its application in Positron Emission Tomography (PET) Imaging. This project, as well as frequent visits to Monash Biomedical Imaging, had sparked my interest in wanting to pursue this field of radionuclide imaging further. I look forward to being part of this interdisciplinary CDT programme where I will be able to enhance my knowledge of this fascinating field, as well as gaining a variety of new skills.

Project: New imaging methodologies for receptor-targeted therapies

During my MEng in Biomedical Engineering at Imperial College London, I became interested in applying machine learning to medical applications. I graduated in 2020, and with the ongoing pandemic, I had the opportunity to work on Imperial’s REal-time Assessment of Community Transmission (REACT) study. My work involved developing an image processing pipeline to analyse their dataset of 600,000+ images of Lateral Flow Immunoassays submitted by study participants.

As part of the Centre for Doctoral Training in Smart Medical Imaging, I am excited to work with Philips Healthcare Research on quality-controlled stress perfusion cardiac MRI. Our aim will be to make the process more robust and reliable for use in the clinic.

Project: Robust quality-controlled quantitative stress perfusion cardiac MRI

I graduated from the University of Bristol in 2021 with a master of engineering degree in Electrical and Electronic Engineering. In my master thesis, I worked on the super-resolution of intravascular ultrasound for coronary arteries. I tried to solve this problem with a deep-learning-based approach. During my undergraduate degree, I picked up a keen interest in magnetic resonance imaging and neurological disorders. Currently, I am conducting a PhD on multi-transmit technology for optimal magnetic resonance imaging of patients with deep brain electrodes under Dr Ozlem Ipek’s and Prof Jo Hajnal’s supervision at Kings College London.

I received my BSc degree in medicine in 2018 and ultrasound technician in point-of-care ultrasound in 2019. I worked on clinical trials and ultrasound-related studies for 2 years at Oxford University Clinical Research Unit (OUCRU) then moved to research in artificial intelligence in medical imaging for the past years in VITAL (Vietnam ICU Translational Applications Laboratory) project, particular in ultrasound image classification, segmentation, quantification, AI-guidance in ultrasound imaging modality.

In 2020, I was awarded a King’s College London-OUCRU scholarship funded by Wellcome Innovations Flagships and I an currently a PhD student under the supervision of Dr Andrew King, Professor Reza Razavi and Dr Alberto Gomez. My PhD project aims at investigating the clinical utility and usability of AI-enabled ultrasound technology in a resource limited ICU setting.

I graduated from the Federal University of Campina Grande (UFCG) in Brazil in Electrical Engineering in 2016. During my undergraduate programme, I was awarded a year of an exchange programme at Western University in London, ON, Canada. For fourteen months, I attended two terms in the institution where I took courses for medical imaging and worked as a summer undergraduate researcher. Recently, I was awarded a diploma of M.Sc. in Computer Engineering from the State University of São Paulo in September of this year. During my master’s, I was awarded an internship at the Translational Imaging Group in UCL for six months, which I worked with diffusion MRI.
Throughout my short academic career, I developed a strong knowledge in deep-learning for medical imaging analysis which resulted in being accepted as part of to King’s College London CDT team where I am currently doing my Ph.D. research applying deep learning approaches to diffusion MRI for neuronavigation.

I graduated from Durham University in 2017 with an MChem degree, where I completed my first research project on synthesising a new responsive PARASHIFT probe for MRS and first developed my interest in imaging chemistry. I then proceeded to work for a medical devices manufacturer for 4 years as a Project Lead, where I was immersed in the healthcare industry. During this time, I also completed my postgraduate MRes degree in Organic Chemistry: Drug Discovery at University College London (2020). My research project at UCL was aimed at evaluating [18F]FPEB PET tracer as a tool for detection of early pathology in cerebellum of Alzheimer’s patients.

My research project at the CDT will focus on synthesis of multimeric nanoparticle-based MRI agents for detecting the role of platelets in Atherosclerosis under Dr Stasiuk’s and Dr Wilton-Ely’s supervision. The aim is to investigate platelet role in atherosclerosis plaque formation and rupture and to develop a tool for predicting plaque formation/rupture in coronary artery disease.

Project: Synthesis of multimeric nanoparticle-based MRI agents for detecting the role of platelets in Atherosclerosis

I graduated from King’s College London in 2020, after completing a degree in Biomedical Engineering. While studying, I had the opportunity to spend time in clinical environments. From this, I developed a keen interest in clinical engineering, particularly in medical devices. I currently have a studentship in the Centre for Doctoral Training in Surgical & Interventional Engineering. My research focuses on affordable technologies for low- and middle-income countries (LMICs). My project aims to result in the creation of a novel, affordable, medical device, capable of improving the safety of surgery globally.

I received my master’s degree from University College London in Robotics and Computation in 2020. I followed this with an Erasmus Mundus Masters Programme in Image Processing and Computer Vision at three partner universities in Hungary, Spain and France. My master’s project was on fetoscopic mosaicking using deep learned optical flow fields. I am currently a PhD student in the EPSRC CDT in Smart Medical Imaging, supervised by Dr Miaojing Shi and Prof. Tom Vercauteren. My PhD project exploits multi-task learning for endoscopic vision in robotic surgery.

Project: Exploiting multi-task learning for endoscopic vision in robotic surgery

I studied physics before training as a clinical scientist, working in a hospital in Brighton and specialising in nuclear medicine. Since qualifying, I’ve worked in a research role at The Royal Marsden/Institute of Cancer Research. The projects and clinical trials I was involved in attempted to optimise molecular radiotherapy using patient-specific imaging and dosimetry. In my PhD I will continue this work in a pre-clinical setting under the supervision of Dr Samantha Terry, attempting to develop and radiobiologically characterise the novel radiopharmaceutical 212Pb for the treatment of neuroendocrine tumours.  

Project: Development, radiobiological assessment and dosimetry of radiopharmaceuticals emitting alpha and beta particles

In 2020 I graduated from the University of Sussex with a First class MPhys degree in Physics with Astrophysics. My initial research exposure in the healthcare field was in 2019, where I analysed medical data of patients associated with dementia, supervised by Dr Elizabeth Ford. I conducted my final year project in the field of diffusion MRI, under the supervision of Prof. Mara Cercignani. In this project, I applied machine learning techniques to improve the resolution of diffusion MR images of the hippocampus area. This led to my growing interest in medical imaging, and of the uses AI can have in this field. I am looking forward to expanding my knowledge in deep learning and its applications in medical imaging.

Project: Deep learning for diagnosis of congenital heart disease in fetus using MRI and ultrasound.

I received my Bachelor’s degree in Engineering from the Australian National University and then completed my MRes degree in Medical Robotics and Image Guided Intervention at Imperial College London. My research project mainly involved CT volume data segmentation, which automates and supplies an essential pre-operative knowledge to achieve intraoperative 3D navigation for robot-assisted minimally invasive surgeries. During my postgraduate studies, I discovered my research interests in computer-assisted medical image analysis and image guided intervention, so after graduation I worked as a Research Assistant at King’s College London and decided to pursue a PhD with Professor Tom Vercauteren at King’s. My current research project involves developing real-time machine learning based data super-sampling and reconstruction algorithms to recover HSI snapshot data with limited resolution.

In 2017 I graduated from the University of Southampton with a BSc in Computer Science with a focus on Machine Learning. Following that, I have finished with a First the MRes Biosciences – Computational Biology at UCL under the supervision of Dr Jorge M. Cardoso and Dr Parashkev Nachev exploring the additional signal found through the interaction between blood analysis and CT images in discriminating between cognitively intact and delirious patients. My interests are laying at the interaction between Machine Learning and Medical Imaging, specifically in creating new Machine Learning techniques for Neuroimaging, and thoroughly using statistic models and analysis for exploratory projects in the field of Neurology.

Project: SmartEHR: predicting patient outcomes live from imaging and non-imaging EHR data

I graduated from Imperial College London in 2022 with an MSci in Chemistry. In my final year of university, I completed a Master’s Project under the supervision of Dr. Philip Miller on synthesising fluorine-18 radiotracers targeting PD-L1 and so my interest in biomedical imaging of cancer was sparked. Therefore, I am extremely excited to continue my research into PET imaging whilst on the interdisciplinary CDT programme. I look forward to developing my research skills and learning more about how chemistry can be used to improve people’s health.

Project: New Chelators for Less-Developed and ‘Heavy’ Radioactive Metal Isotopes

I graduated with a bachelor’s degree in optical information science and technology from Dalian University of Technology in 2017. During my undergraduate studies, I took part in a project aimed at using surface enhanced Raman Spectroscopy to realise serum test, from which I found my interest in exploring conventional diagnosis technology of diseases. After graduation, I became a graduate student of Washington University in St. Louis and obtained a master’s degree in Electrical Engineering there in 2019. I became familiar with image processing and its potential clinical applications during that period.
Due to my former study experiences, I decided to make efforts to develop a conventional imaging technique as well as apply this technology to medical diagnosis and treatment. Thus, my research interest mainly focuses on developing a photoacoustic endomicroscopy probe which is applied to tumor tissue imaging.

I received my Bachelor’s degree from Ocean University of China in 2020 and have several projects using fibre optic sensors for multi-parameter sensing. In 2021 I graduated from the University of Glasgow and the University of Edinburgh with an MSc in Sensor and Imaging Systems. During this time, I discovered my strong interest in medical sensors, especially for applications in cardiovascular disease monitoring. So In my PhD, I will mainly focus on the research of wearable biosensors and machine learning for cardiovascular disease monitoring and alerting. This will be an interdisciplinary project and I look forward to collaborating with more people to explore more possibilities and hopefully in the future we could help more people in need.

I have recently graduated from UCL with an MSc in Advanced Biomedical Imaging in 2018. I have decided my research interest on MRI from my MSc. research project that concerns about the translation of hepatic Arterial Spin Labelling (ASL) to the clinic. I do find this interesting and I would like to pursue advanced study on imaging acquisition and registration on real clinical problems.
This CDT programme includes a number of modules across all the disciplines, together with the professional technical training, it is designed to set us on the road to becoming the expert in the research field in biomedical imaging. I am excited to become one part of CDT group and have the opportunity to take such a fascinating project.

Project: AIM: advanced imaging of bone marrow in myeloma with CT & MRI

I graduated with a MSci degree in Chemistry with Medicinal Chemistry from Imperial College London in 2017. I did my masters project in the group of Prof Ed Tate, designing novel binders for the Rab27a protein. During the course and project, I learned a great deal about the chemistry of the cell and how it can be visualised. Throughout the course I developed an interest in how imaging techniques can be used to further improve our understanding of how the chemistry of the cell works.

Project: Imaging and sensing in living cells using dual modality fluorescent PET imaging agents

I graduated with a BSc in Biology from University of Northampton in 2017 and went on to graduate with distinction from Queen Mary’s University of London in 2019 with an MSc in Bioinformatics. In this time my focus was evolutionary and population genetics, creating a novel method of simulating genetic evolution in haplodiploid populations. With a keen interest in the applications of machine learning methods to genomic analyses, in January of 2020 I started my PhD here at King’s College London. My project examines the relationship between genotype and phenotype in cardiac electromechanical function, led by both Professor Alistair Young (King’s College London) and Professor Patricia Munroe (Queen Mary’s University of London, WHRI), funded by the EPSRC DTP.

In 2020 I graduated from Imperial College London with an MSci in Physics. At an early stage in my degree I decided to apply my physics knowledge in the medical field. As a result, my Master’s project was focused on improving spatial resolution of a novel non-invasive brain stimulation technique called temporal interference. In my PhD, I will be applying machine learning to improve ultrasound images.

Project: Next generation of ultrasound imaging using ultrafast acquisition and machine learning

In 2019 I graduated from Imperial College London with an MEng in Maths and Computer Science. Until my last year I’d wanted to become a software engineer – then in my Masters year, and after two software internships, I undertook a project with Bernhard Kainz titled Tackling Crohn’s Disease with Deep Learning. I discovered that my passion instead lay in applying data science to medical problems. I presented this research at MICCAI PRIME, and can’t wait for more opportunities to interact with the scientific community over the course of my PhD.
So far the CDT has immersed me in a network of researchers across many disciplines, and increased my awareness of other fields. I’m looking forward to beginning my PhD on age-related macular degeneration in OCT images.

Project: Early detection and diagnosis of age-related macular degeneration AMD using machine learning

With a background in Chemistry, I graduated with my MChem in July 2022 from the University of Warwick. During my final year, I completed a research project under the supervision of Professor Peter Sadler and Dr Cinzia Imberti related to development of a novel photoactivatable Pt(IV) metallodrug with applications in anti-cancer therapy. This year of experience in lab-based research proved invaluable in understanding where my interests lay for further exploration.
Much of my previous project work centred on the broad topics of synthetic inorganic and medicinal chemistry and, along with some of the lecture-based content from my undergraduate degree, allowed me to gain greater appreciation of medical imaging and its involvement in cancer treatment. Thus, my aim is to continue to expand my knowledge of this broad and exciting research topic through the CDT – focusing particularly on medicinal inorganic chemistry and radiochemistry for both diagnostic and therapeutic application.

I graduated from Swansea University upon completed my MSci in Computer Science in 2017. Having worked for awhile as a software developer I decided that I much preferred taking part in projects that I had a strong interest in and that completing a PhD would be an excellent way to achieve this while also attaining a higher academic accreditation. My current areas of interest include; machine learning, deep learning and neuroscience, which my project should give me excellent opportunities to investigate.

Project: Individualised clinical neuroimaging in the developing brain: Learning cortical development

I am a PhD student, studying preprocessing and data analysis pipelines for functional near-infrared spectroscopy (fNIRS) data. I will be working on data from the INDiGO Trial, as part of Dr Sophie Moore’s research group. The study aims to investigate the effect of micronutrient intervention on brain development during infancy up to 12 months of age, using behavioural assessment, eye-tracking and fNIRS to assess the neurodevelopment and behavioural outcomes.

I completed an MSc in Brain Imaging at the University of Nottingham in 2018, building on an MMath in Mathematics. In the intervening years I taught mathematics in Bogotá, Colombia.

In 2017 I graduated Imperial College London with a MEng in Computing (Games, Vision and Interaction). Following a successful Master’s project with Dr Bernard Kainz and Dr Emma Robinson, as well as enjoying several modules related to Human Brain functionality and how we understand it, I have developed a keen interest in Medical Imaging and Medical Image Visualisation, in particular for understanding the structure and behaviour of the Human Brain.
I look forward to my time at the CDT working with people from many different disciplines to further our understanding of ourselves.

Project: A service-oriented architecture approach for collaborative and quality assured analysis of medical image data

In 2020, I completed my Bachelor’s in Biomedical Engineering with Industrial Placement with City, University of London. During my degree, I undertook a placement year with Great Ormond Street Hospital, where I had the opportunity to work with a wide range of medical devices in a clinical environment and to identify the importance of implementing AI technologies to solve real-world problems. The applications of machine learning in the healthcare industry are never-ending and the advancements have been increasingly significant. For this reason, I have decided to pursue a PhD with the EPSRC DTP programme at King’s College London, which will equip me with an outstanding set of skills to bridge the gap between AI and healthcare technology. My keen interest in fetal/pregnancy development has led me to choose a project on the development and implementation of an MRS method which enables the profiling of metabolite concentrations in the fetal brain irrespective of fetal and maternal movement, increasing the success rate of fetal cerebral MRS examinations and facilitating the adoption of this tool into clinical routine fetal evaluation alongside other advanced MR methods.

Project: Motion-robust metabolite quantification in the fetal brain with MR spectroscopy

I graduated with an MSci in Chemistry from Imperial College London in June 2017. My Masters project was in Dr. Rob Davies’ group studying the mechanism of Cu(I) catalysed coupling of acidic heterocycles to iodobenzene. After finishing my MSci, I worked as a marketing analyst in Deliveroo for the rest of 2017, then went travelling around the Pacific Rim in 2018. Working temporary jobs in Auckland for three months, then travelling around New Zealand, Fiji, Japan and California. For the past year, I have been working as a data analyst/consultant at an analytics start-up/consultancy in London, and now I’m back to academia, in Professor Nick Long’s group studying smart Manganese-based dual modal PET/MRI probes.

Project: Smart manganese-based dual-modal PET-MRI probes

I am currently a 1st year PhD student in King’s College London, and I obtained my Msc Degree and BEng Degree in Communication & Digital Signal Processing Group of Imperial College London and Electronic Information Department of Sichuan University respectively.
I felt so inspired by the way the professors here taught, and became very curious about all the mathematical proofs, models ever since then for their preciseness and rationality. I used to learn some basic conceptions about biologic signal processing like respiration in Spectrum Analysis & Adaptive Signal Processing course and gained a deeper understanding about how to process magnetic resonance image (MRI) during my current project, in addition, I also have some MATLAB programming experiences about machine learning thanks to my undergraduate thesis.
I do wish to use all the knowledge I have so far to make some contribution to biomedical area especially about women’s health and have the willing to learn something new. And my current project under Prof Kawal Rhode’ supervision is: Development of Image-based Device Tracking in Transoesophageal Echocardiography for Surgical Guidance.

I’m a radiology registrar, pausing my clinical training for a PhD. I graduated from Medicine at King’s in 2015, and also did my iBSc in Imaging Sciences here. I completed my MRes in Medical Robotics and Image Intervention at Imperial in 2018, where I used deep learning to model outcomes in simulated vascular intervention. My research interests are in brain imaging and machine learning.

As an undergraduate student, I started my studies in mathematics, physics and computer science in 2013 with an intensive foundation degree (French Classes Préparatoires) at the Lycée Henri IV in Paris, France. Upon completing these studies in 2015 with a competitive examination, I was selected to join Telecom Paris in 2016, a French engineering Grande École specialised in computer science and mathematics. At Telecom Paris, my studies were focused around Data Science, Image Processing and Applied Mathematics. After obtaining my Engineering Master’s Degree, I moved to London in 2018 to undertake a M.SC. in Machine Learning at Imperial College London. For my master’s thesis, I developed a deep learning framework to detect CPA – a pulmonary infection caused by a fungus – from lungs CT scans in a weakly supervised way. This project took place under a partnership between the Royal Brompton Hospital and the Imperial Biomedical Research Centre. I spent the last year acquiring valuable professional experience as an artificial intelligence developer focusing on Computer Vision research, in the Huawei UK CV Research Center. Upon being accepted at the CDT in Smart Medical Imaging, I am honoured to join Dr Emma Robinson’s team to work on a project focused on applying deep learning on brain surfaces from neonatal fMRI data, to predict neuro-development outcomes.

Project: Reading minds with Deep Learning: predicting behavioural states from functional imaging data

I graduated in Biomedical Engineering at King’s College London in 2018. I have always had a strong passion for maths and physics and the possibility of combining them with computing and programming to solve medical problems brought me to apply to this CDT. During my final year, I developed a novel 3D electro-mechanical framework of the atria to assess atrial fibrillation which persuaded me to continue the research on this topic.
In the four years to come, I will explore cardiac computational modelling further, improve and strengthen the knowledge acquired during my undergraduate and get to know and work with a whole group of amazing students and researchers.

Project: Automated detection of cardiac arrhythmia locations to optimise treatments using a combined physics and machine-learning approach

During my MSci Chemistry degree at Imperial, I had the opportunity to work on a number of projects of my own design. My primary interest is in molecularly imprinted polymer nanoparticles (nanoMIPs), a class of robust synthetic receptors with highly controllable properties. My previous projects involved using these nanoparticles as synthetic recognition elements in the design of novel assays, and I believe that the next step is to use them for in vivo applications. As an affiliated student working on a PhD at Imperial funded by a joint President's Scholarship and MRC DTP Studentship, I hope to benefit from the wealth of experience and state-of-the-art facilities offered by the EPSRC Centre for Doctoral Training in Medical Imaging

Science with Data Analytics, alongside a freelance career in both data analytics and the music industry. My Masters research focused on using Neural Networks for Music Information Retrieval. I have recently completed a Masters degree at the University of York in Computer My PhD research focuses on the utilization of Natural Language Processing and Deep Learning to detect disease recurrence in patients previously treated for cancer. I am passionate about the application and implementation of artificial intelligence for the benefit of public health and well being.

I graduated from King’s college London with an MEng in Biomedical Engineering and, during my studies, I found the CDT offering projects in MRI as well as implementation of Deep learning and these are topics that were of high interest to me, leading me to apply to the CDT program.
While on the MEng I worked on the use of deep learning to segment myelin-like signals from foetal brains as well as studying myelination relations in them.
Overall, I wish to go further into MRI and smart imaging research and learn skills on the CDT and in my PhD that will help me understand these topics better.

Project: Quantitative mapping of developing fetal organs using dynamic MRI and artificial neural networks

I previously studied at The University of Manchester where I received a MChem degree in Chemistry. My Masters project was carried at Manchester Institute of Biotechnology and involved research focused on cell-targeting magnetic nanoparticles for theranostics. I then went on to spend a year working at Edinburgh Molecular Imaging LTD, a clinical phase biotechnology company focused on enabling image guided therapy. Here my passion for research into the diagnostic and therapeutic applications of medical imaging probes was sparked.
I hope to continue this interesting research and develop my knowledge further within the Wilton-Ely Group.

I received my BSc degree in Electrical Engineering from the University of Witwatersrand, South Africa in 2010. I worked in a few industries before coming back to academia to study my MSc in Biomedical Engineering at the University of Cape Town. My thesis focused on automated feature detection from ultrasound images to improve the diagnostic pathway for Hodgkin’s Lymphoma as it is often mistaken for TB and HIV within Africa. I currently have a DRIVE-Health studentship and my PhD project aims to develop an artificial intelligence (AI) decision support tool that can use big data to assist cardiologists in making better decisions about treating heart failure patients.

I previously completed my undergraduate degree in Medical Biochemistry, followed by employment in an NHS Nuclear Medicine department where I was involved in aseptic radiopharmaceutical production, administrations of diagnostic and therapeutic radiopharmaceuticals, as well as performing a variety of image acquisitions. I have also worked in a dedicated PET centre, in the synthesis of 18 F-labelled radiotracers for research and clinical use. My experience in a clinical environment underpins my desire to work in translational research, and the multi-disciplinary approach of the DTP will equip me with the skills to work in this field.

Having spent the last five years working in medical physics for the NHS, I have become acutely aware of the potential for artificial intelligence to transform patient care. However, for this potential to be realised, annotation of large datasets is typically required, a process which is often highly resource intensive, especially in the development of deep learning-based image segmentation tools. During my time as an MRI Physicist at the Royal Marsden Hospital, I discovered this reality first-hand while manually segmenting over 100 whole-body MRI scans. This experience has made me highly motivated to develop AI solutions that significantly accelerate the task of image segmentation.

Project: Active and continual learning strategies for deep learning assisted interactive segmentation of new databases

I’m a Paediatric Cardiologist, with a special interest in Fetal Cardiology. I’ve undertaken my specialist training in London, Oxford, and Melbourne, and I received my CCT in 2019. I’ve just enrolled in an MD(Res), looking at ways of using artificial intelligence to improve the antenatal detection of congenital heart disease, which I hope will translate into better outcomes for these babies after they are born.

In 2019, I graduated from the University of Liverpool with an MChem degree in Medicinal Chemistry with Pharmacology, with my master’s project focussing on the synthesis of PROTAC compounds for breast cancer. My past research experience has led to my interest in the development of targeted therapeutics and diagnostics.

My PhD project, in collaboration with AstraZeneca, will explore the imaging-guided development of polysarcosine-based drug delivery systems, to address the rise in anti-PEG immunity. We aim to better understand the properties of pSar, to inform the development of novel nanomedicine-based drug delivery systems

Project: Imaging-guided Development of Polysarcosine-based Drug-delivery Systems

I graduated in Biomedical Engineering in 2019 from the Universitat Pompeu Fabra in Barcelona. During my undergraduate studies, I didseveral internships working mostly on cardiac computational modelling. I also had the opportunity to work on my bachelor’s degree finalproject during seven months in Philips Research Paris – Medisys about numerical modelling the aortic and mitral valves. I’ve recentlygraduated from the Healthcare Technologies MSc at King’s College London, with special interest in medical image computing, deep learningand cardiac computational modelling. My research interest focus mostly on the combination of artificial intelligence technologies and computational modelling to improveunderstanding of cardiovascular disease, as well as improving diagnosis and treatment planning. Those interests have motivated me intopursuing a PhD where I will work on an intra-operative planning software for improving congenital cardiac surgery.

I acquired my diploma (equivalent to MEng) in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2017. Coming from a family of doctors, I have always been fascinated by research related to medicine and health but from a technical perspective that involves mathematical and engineering modeling. My research interests include advanced signal processing and machine learning techniques applied to medical data.
I believe that the CDT’s interdisciplinary approach to medical imaging provides the perfect setting for me to explore these areas and gain valuable insight that will allow me to contribute to the inspiring field of biomedical engineering.

Project: Deep learning for early detection of lung cancer in patients at risk

I graduated in Biomedical Engineering in 2016 from the Polytechnical University of Madrid. In my fourth year, I specialised in Medical Imaging and did my final project in collaboration with the Guttmann Neurorehabilitation Institute, helping to incorporate eye-tracking techniques to Neurorehabilitation tasks.  After working for two years in industry, I decided to return to academia by completing a Master of Science Degree in Bioengineering and Neurotechnology at Imperial College. My Master thesis, supervised by Dr. Andrew Scott, involved the application of deep learning algorithms to denoise Cardiac Diffusion Tensor images. The project made me want to continue working with Deep Learning, as I believe it has a vast potential application in Medical Imaging.  On the other hand, the human brain has always been a fascinating topic for me, and thus I have always wanted to focus my career as a Bioengineer in Neuroimaging. For these reasons, and because I want to keep learning and developing my skills, I joined the CDT, where I will be working on the generation of a diseased human brain atlas with Deep Learning, under the supervision of Dr. Jorge Cardoso and Prof. Tom Vercauteren.

Project: A generative model of the diseased human brain

In 2014 I graduated from Kings College Londonwith a BSc in Pharmacology with extra-mural year at Imanova centre for imaging sciences. Here I developed a keen interest for Neuroimaging using PET-CT. Having completed my degree, I went on to work with professor Michael Marber in the cardiovascular division of the Rayne institute at KCL where I was part of a drug discovery project working in the fields of molecular biology and Biophysics. I then spent a year 1:1 with patients working in St George’s hospital as a healthcare assistant in oncology and palliative care as I wanted to understand better how science translated to the clinical setting.
Having had this experience, I have now chosen to direct my focus towards cancer imaging at King’s College on this CDT program to combine my interest in imaging with the wish to better understand a disease that affected the people that I have most closely worked with.

Project: Macrophage cell tracking with PET using zirconium-89

I have completed a MEng in Mechanical Engineering and six months of PhD research in the Graduate School of Medicine at Chiba University, Japan. My bachelor’s thesis involved 1-D computational modelling of haemodynamic, while my master’s thesis focussed on coupling the autonomic nervous system with a 0-1-D haemodynamic model. During my Master’s, I also conducted a project using 3-D computation for the optimisation of coronary artery surgery with doctors in Chiba University Hospital, Japan. The six months of PhD research evaluated methods of statistical analysis for the dietary patterns and PCB contamination in pregnant women. I aim to pursue a career in biomedical engineering, I have recently moved to London to grasp an opportunity which will broaden my horizons and allow me to reach my goals and ambitions while meeting and working with renowned researchers in the field.
Project: Assessing endothelial function by analysing non-invasive pulse waveforms: a computational and in-vivo based study
This project will develop and implement our exciting 1-D computational solver (Nektar++:www.nektar.info) to analyse the effect of medication on endothelial function. Detailed analyses of cardiovascular imaging data on rabbits along with measured vital data (e.g. blood pressure and blood flow) will be used. Furthermore, human vital data from the clinical database and the vital data of a virtual population generated by Nektar++ will be used for the assessment of endothelial function.

I graduated with an MSci in Chemistry from Imperial College London in June 2020, having carried out my final year project on the synthesis of a FRET-based reporter probe for the enzyme activity of heme oxygenase-1 under the supervision of Prof. Nick Long. I have also carried out summer research on charge carrier dynamics in lead-halide perovskites using ultrafast laser spectroscopy under the supervision of Dr. Artem Bakulin. My current project involves the synthesis of new MRI/optical imaging probes and their delivery to targets in the brain using a combination of focused ultrasound and microbubbles for blood-brain barrier opening.

Project: An acoustic wavelet technology for delivering smart imaging probes to the brain

I completed my Bachelors in Biomedical Engineering at King’s College London in 2015, during which time I worked on respiratory motion models for image-guided interventions. The following year, I completed a 12-month placement at Siemens Healthcare in Germany where I focused my research on image denoising and contrast enhancement techniques to improve device visibility in X-ray fluoroscopy sequences. I also acquired my MSc in Machine Learning at Imperial College London in 2017. There, I had the opportunity to work on a self-proposed project in tensor decompositions for large-scale data.

Now, I am pursuing a CDT in medical imaging with the hopes of applying statistical models of anatomy and function that automatically extract diagnostic and prognostic biomarkers from echocardiographic sequences.

Project: Learning the signature of disease in echocardiography

I received my Master’s degree from Huazhong University of Science and Technology in 2021, supervised by Professor Xiang Bai. At that stage, I got involved in some exciting research projects and contributed to papers in top-tier conferences about image segmentation, deep learning models, and generative adversarial networks.

Thanks to these research experiences, I found the pleasure of computer vision and deep learning; the research of computer vision in medical has strong practical value and huge potential. Considering my relevant knowledge and skills, I chose to pursue a PhD at King’s College London under the supervision of Professor Sebastien Ourselin and Professor Prokar Dasgupta.

I started university in 2014 at the Catholic University of Leuven, where I obtained my B.Sc. in Mechanical Engineering. Thereafter, I obtained a M.Sc. in Biomedical engineering, during which I spent one year in Montreal as part of an exchange program. Next to my studies, I was active in different areas: I have tutored for academic courses. Furthermore, I was a member of ‘Bloedserieus’, an organisation enabling blood donations for students and I was part of the Product Innovation Project (PiP). During my master thesis, I worked on cardiac MRI and collaborated with the Radiology department and the Medical Imaging Research Centre (MIRC). In my PhD, I will continue working on MRI physics, more specifically neonatal MRI at 7T within the Department of Perinatal Imaging and Health.

Project: Enhanced neonatal brain development MRI at ultra-high field

My name is Yaqing Luo. I graduated from the London School of Economics and Political Science in 2020 with a BSc in Mathematics with Economics, and also in 2021 with an MSc in Applicable Mathematics. I had the opportunity to participate in a few research projects, and in this process, I have become more interested in engineering and different applications of Artificial Intelligence and Machine Learning. After reading more on medical imaging, I am very much looking forward to studying at King’s College London for an MRes in Healthcare Technologies, where I would be able to see more possibilities in combining medical imaging and machine learning methods.

Project: Concurrent multi-task learning-based deep convolutional neural networks for high resolution assessment of in-vivo cardiac microstructure

Originally from China, I graduated with a first class BEng (Hons) in Mechatronics and Robotics Engineering from the University of Birmingham in 2022. I developed a keen interest in biomedical engineering during my final year project, where I developed an electronic bidomain model of human heart to simulate the action potentials of ventricular cells and the electrocardiogram.

Under the support of K-CSC scholarship, I am currently a PhD student at King’s College London, where I focus on the movement control and haptic feedback of Ultrasound robot arm. The CDT in Smart Medical Imaging is a great opportunity for me to broaden my skills and pursue my research in this field.

I earned a BSc in Applied Mathematics and a BSc (Hons) in Mathematics with Financial Mathematics through a joint programme between Anhui University and the University of Manchester in 2020. I then received an MSc in Machine Learning from University College London in 2021. My field of interest is applying machine learning techniques to the biomedical field. Specifically, I am interested in developing automated ways to efficiently detect abnormal symptoms in medical images. In my PhD project under the supervision of Prof. Alistair Young, Dr. Steven Niederer, Dr. Michiel Schaap, and Dr. Matthew Sinclair, I will focus on developing a deep-learning-based multi-modal spatio-temporal atlas, which will allow rapid co-registration of patient cardiac anatomy between different modalities.

Project: MultiHeart: Fusing CT and MRI with Space-Time Transformation Networks

I graduated with an Electrical Engineering degree from Xiamen University of China in 2017 and got a Master’s degree in Electrical Engineering from Xi’an Jiaotong University of China in 2020.

​During my learning process, I joined Robot Innovation Lab of Xiamen University and was responsible for the design of driving circuit and the development of sensor used for robots.

I am currently studying Biomedical Engineering and Imaging Science Research. I would like to have a positive impact on health care, whilst retaining a focus on engineering. My research interests include haptic perception and control, particularly distributed tactile sensing.

I graduated from the University of Leeds with a Bachelor’s in Neuroscience. For my Final Year Project, under Professor Jim Deuchars, I studied the effect of GABA on neurogenesis in the post-natal spinal cord. Following this, I joined the neuromarketing company Neuro-Insight, where I conducted Steady State Topography research to benefit the advertising strategies of commercial clients. I then worked for the tech startup Brainlabs where I represented ‘Bulb’ and ‘Formula 1®’ to implement digital marketing strategy through Google and Facebook APIs. After studying neuroimaging and automation in the private sector, I am very excited to return to research, enhancing my understanding of the use of machine learning to analyse neuroimaging techniques and the potential applications of these to the modulation of brain dynamics.

Project: Engineering simultaneous EEG-fMRI for image guided modulation of brain dynamics

I graduated from Imperial College London with an MRes degree in Medical Robotics and Image-Guided Intervention in 2019. I had previously received my bachelor’s degree in Mechanical Engineering from the University of Birmingham in 2016. My research interests include sensing, navigation, and control on flexible robots including continuum robots and soft robots. Currently, I am working on developing a robotic system to perform the intervention of the ductal networks based on soft growing robots.

I originally studied Chemistry at Christ Church, University of Oxford, where I conducted a final year research project on macrocycle synthesis under the supervision of Professor Stephen Faulkner. For my PhD project, I worked under Professor Nick Long and Dr Rick Southworth on synthesising and radiolabelling gallium-68 chelators with a view to mitochondrial imaging. These chelators were then assessed in a variety of biological systems, including in cancer and cardiac tissue. I would recommend the CDT to anyone looking to expand their horizons and undertake their PhD in a highly interdisciplinary setting; I personally was able to learn biological analysis techniques as well as analyse my work using Python. Since graduating in 2019, I have been working at Lloyds Banking Group in their Market Risk division, where I am able to use the coding and analytical skills I developed through my time with the CDT in a new and exciting field for me.

Publications:

Synthesis, gallium-68 radiolabelling and biological evaluation of a series of triarylphosphonium-functionalized DO3A chelators; Adam J. Smith, Peter J. Gawne, Michelle T. Ma, Philip J. Blower, Richard Southworth and Nicholas J. Long; Dalton Transactions, 2018, 47, 15448-57 (doi: 10.1039/C8DT02966K)

DO2A-based ligands for gallium-68 chelation: synthesis, radiochemistry and ex vivo cardiac uptake. Adam J. Smith, Bradley E. Osborne, George P. Keeling, Philip J. Blower, Richard Southworth and Nicholas J. Long; Dalton Transactions, 2020, 49, 1097-106 (doi: 10.1039/C9DT02354B)

Project: New gallium chelates for imaging apoptosis and the mitochondria

I have completed my Bachelors in Biomedical Engineering in 2015 from Kings’ College London. During my study at Kings’ I have worked on projects involving the use of computational modelling combined with imaging techniques to investigate cardiac disorders. My key interest areas of research in medical imaging are mathematical modelling and image acquisition techniques. The CDT will provide me with an opportunity to learn more and gain experience on these modern research tools. During my PhD I hope to use these techniques extensively to develop new ideas which would contribute to improve human health.

Publications

Development of a Deep Learning Method to Predict Optimal Ablation Patterns for Atrial Fibrillation
Muffoletto, M., Fu, X., Roy, A., Varela, M., Bates, P. A. & Aslanidi, O. V., 1 Jul 2019, 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019. Baruzzo, G., Daberdaku, S., Di Camillo, B., Furini, S., Giordano, E. D. & Nicosia, G. (eds.). Institute of Electrical and Electronics Engineers Inc., 8791475

Image-Based Computational Evaluation of the Effects of Atrial Wall Thickness and Fibrosis on Re-entrant Drivers for Atrial Fibrillation
Roy, A., Amaral Varela, M. M. & Aslanidi, O., 4 Oct 2018, In : Frontiers in Physiology. 9, 1352.

Image-based computational evaluation of the competing effect of atrial wall thickness and fibrosis on re-entrant drivers for atrial arrhythmias
Roy, A., Varela, M. & Aslanidi, O., 2017, In : Computing in Cardiology. 44, p. 1-4 4 p.

Project: Imaging and computational tools for catheter ablation treatment of atrial fibrillation

In 2017, I graduated from Cardiff University with a Masters in Chemistry with a Year Abroad. During my third year, I travelled to the University of Toronto and worked for Prof Patrick Gunning, focusing on medicinal chemistry and organic synthesis, investigating the inhibition of the E1 activating enzyme UBA5. For my final year project, I worked for Dr Rebecca Melen looking investigating the use of phosphorus containing Lewis acids, and their potential use as catalysts for organic various reactions.

I hope to further develop my knowledge and gain the skills to equip me for a career in research during my time at the CDT.

Project: Radiobiological assessment of radionuclide pairs used in theranostic (imaging and therapy) approaches

I have recently finished four years of studying physics at the University of Nottingham. In my third year I studied some medical physics modules with the focus on CT and MRI. Following these modules, I became very interested in imaging, MRI in particular. I also got to observe MRI scans and what can be achieved with them, it was then that I decided that this is what I want to do.
I am very excited to start the CDT, to learn new skills and to have the opportunity to do such an interesting project.

Project: Fetal quantitative flow measurement by MRI

I’ve recently finished my PhD studies at the Biomedical Engineering Department at KCL under the supervision of Dr Claudia Prieto and Professor Andrew Reader. My research focused on the development of techniques for motion correction in cardiac PET-MR imaging. A typical PET-MR examination takes about 15 minutes, and during that time the heart is continuously moving due to the respiratory and cardiac cycles. If the motion of the heart is not compensated for, we obtain blurred images that cannot be used to make accurate diagnoses or therapy decisions for cardiac diseases. During my PhD, I developed a framework that allows us to measure the cardiac and respiratory motion from MR images, and then uses this information to correct both the PET and MR data so that the final images are focused and small features such as the coronary arteries can be well depicted. I am currently working as a Research Assistant with Dr Prieto, in a position funded by the Wellcome Trust/EPSRC Centre for Medical Engineering. The aim of our project is to extend the technique developed during my PhD to multi-contrast MR imaging, which will allow us to further advance the clinical translation of our framework.

Project: Multi-parametric PET-MR imaging

After graduating from the Technical University of Madrid in 2016 with a BEng in Electronics Engineering I moved to London, where I received an MSc in Biomedical Engineering from Imperial College London in 2017. As an undergraduate student, I delved into the field of medical ultrasound, with a particular focus on its use for neurological purposes. As a master’s student, I studied ways in which the interaction between neuronal firing and sound could be used to detect brain activity.

Project: High resolution and high contrast imaging and quantification of cardiac macro- and micro- blood flow based on ultrafast ultrasound acquisition and signal processing

I decided to return to the world of academia in 2016 as a PhD candidate in Imaging Sciences and Biomedical Engineering. With previous roles (at world-leading organisations) including Research Officer, Climate Scientist, and Systems Engineer; I hope to bring a diverse range of skills to the CDT. I have also designed and conducted C++ and Python university lecture courses, and hold a Computer Science MSc and Physics BSc from Imperial.
I am particularly excited by interfaces between technology and the real-world, and have a keen interest in interdisciplinary efforts, disruptive data visualisation, and data science in all its numerous interpretations. I hope to pursue these interests further at the CDT, focusing on PET image reconstruction with an emphasis on practical applicability, leveraging GPGPUs and distributed computing.

Project: Advanced and generalised resolution modelling with artefact reduction for high-resolution positron emission tomography

I’m a final year PhD student in Department of Surgery and Cancer at Imperial College London. Before moving to London, I obtained my BSc degree in Pharmaceutical Chemistry, and MRes degree in Pharmacy at Chongqing University, China. My main research interest lies in the development and evaluation of novel PET radiotracers for imaging tumour metabolism and tracking therapy-induced senescence in tumour cells. Cellular senescence is increasingly regarded as a cause of several age-related diseases and tumorigenesis. Therefore, imaging this phenotype by non-invasive PET tracers offers the possibilities of describing the mechanisms underlying senescence-related aging and assessing the efficacy of senescence-inducing therapeutics.

Publications
Development of a Fluorine-18 Radiolabelled Fluorescent Chalcone: Evaluated for Detecting Glycogen
Allott, L., Brickute D., Chen C., Braga M., Barnes C., Wang N. & Aboagye E., May 2020 (Accepted), In: EJNMMI Radiopharmacy and Chemistry

Project: Imaging glycogenesis as a novel biomarker of drug-induced quiescence and senescence

I previously studied Computing at Imperial College London, and for my Masters project I looked into automatic analysis of foetal cinematic MRI scans. This work motivated me to join the CDT so as to work further in this area, with my particular interests lying in computer aided automatic analysis of medical images. 
Having now completed my PhD titled “Image Synthesis in Medical Imaging”, I am taking part in a Knowledge Exchange Program organised by MedIAN. I will be applying and developing some of the methods I have worked on in my PhD to new work in the context of cardiac magnetic resonance imaging, particularly the imputation of missing data using generative adversarial networks.

Project: Machine learning for differential diagnosis of dementia from multi-modality MR and PET imaging

I graduated with a BSc (Hons) in Mathematical Sciences from University College Cork (Ireland) in 2016. This included a year abroad which I spent at the University of California, Santa Barbara. Throughout my degree I was consistently attracted by the potential of the applications of mathematics. Due to the multidisciplinary nature of the US education system, I was inspired to explore the possibility of using my skills to solve problems in other fields, in particular using the computer. This led me to the Tyndall National Institute where I worked as a research intern, writing code to simulate semiconductor lasers. My interest in the applications of mathematics and my desire to undertake a project which can really benefit society is what drew me to medical imaging. With this PhD, I have the opportunity to apply my skills in mathematical modelling and computer programming to develop state of the art technology with a huge potential for clinical impact.”

Project: Advanced analysis of stress perfusion CMR

I have a bachelor’s degree in mathematics from Université Paris Diderot – Paris 7 and a master’s degree in advanced computing from King’s College London. In graduate school I developed an interest in computational physics and machine learning, which led me to the project I’m working on in my PhD—motion modelling for automated assessment of foetal movements. During breaks from university I also interned as data scientist at ASOS.com and RapidMiner, and as quantitative analyst at BNP Paribas.

Project: Automated assessment of fetal movements as an indicator of postnatal neurological health and function

So far during my project, I have investigated existing techniques for myelin imaging in MRI with the primary goal to develop a sequence that has optimum myelin sensitivity and specificity. Due to its tightly-packed molecular structure, myelin often appears invisible in traditional scans. Therefore, more sophisticated quantitative methods are needed to determine its presence and assess the neurological conditions in which myelin has been implicated. Currently, the two techniques I am most interested in are known as mcDESPOT and ihMT. Through simulation studies of parameter estimation accuracy, different search-space visualisation methods and in-vivo data acquisition, we have completed an in-depth analysis of mcDESPOT and its ability to map myelin water. Recent literature studies have highlighted the potential of ihMT for myelin imaging and using novel radiofrequency pulse design, I hope to maximise the myelin contrast obtainable, resulting in a clinically-feasible and informative sequence.

Project: Integrating myelin imaging with diffusion MRI for microstructure modelling

I am a Biomedical Engineer with an MSc from the University of Padova (Italy) and a BSc from the University of Trieste (Italy). I carried out my Master’s project at Columbia University in New York (USA), where I worked on PET imaging and medical data analysis. After the graduation I worked as a research engineer at Vision RT, medical imaging company that develops leading technology in surface guided radiation therapy. Throughout these experiences I strengthen my interest in cancer imaging and PET/MR technology. This multi-modality approach provides multi-dimensional data particularly suited for the fast-growing field of machine learning. Being part of this interdisciplinary CDT gives me a great opportunity to work towards the clinical implementation of my future research findings.

Project: A simple “push-button” PET-MR footprinting method for multi-modality prostate cancer imaging

I graduated with an MEng in Biomedical Engineering from Imperial College London in 2016. My third year project involved working with image processing techniques and exposed me to the potential applications in healthcare, which inspired my particular interest in computer vision. This, alongside my studies, led to my desire to pursue further research in medical image computing through the CDT. I look forward to gaining the skills and knowledge necessary to contribute to this exciting field during my PhD.

Project: Novel biomarkers for liver imaging in the monitoring of cancer therapy

I completed my Bachelors and Masters of Science at the Polytechnic University of Catalonia (Spain) in Biomedical Signal Processing.  In order to expand my knowledge and have an international experience, I enrolled into a double degree programme with Telecom Bretagne (France), where I obtained the French Masters of Engineering and a Research Master in medical imaging. My research interests lie in the fields of Machine Learning and Computer Vision focused on medical image processing and object recognition. More concretely, I am passionate in clinical applications such as non-invasive imaging, navigation and Vascular and Interventional Radiology.

I believe that a PhD at the CDT will empower me to work at the forefront of scientific research and develop excellent domain expertise in imaging science, applying this knowledge to clinical applications with the aim to improve people’s lives. I also believe that doing a PhD in King’s College is a great opportunity to contribute and learn from some of the very best scientists and investigators of the world.

Project: Multimodal analysis of cardiac motion and deformation

I am a graduated student in Chemistry and Pharmaceutical Technology and I obtained my degree in Alma Mater Studiorum, University of Bologna. During the last year I had the pleasure to do an internship at the Department of Imaging Sciences under Professor Antony Gee: the project focused on the development of new specific radiotracers for Alzheimer’s disease. This research led me to my current interest in radiochemistry and imaging of brain diseases.
This is the reason why I feel that the CDT program in Medical Imaging will make me achieve great goals, both under and academical and a personal point of view. In fact, the multidisciplinarity of the project will allow me to improve as a researcher whilst focusing on the subjects that mostly intrigues me.

Project: Novel 11C-methylation strategies and their application in CNS receptor imaging

I graduated from The University of Hull in 2016 with the degree of BSc Biomedical Sciences with first class honours. During this degree, I completed a research project with Dr Graeme Stasiuk on multimodal zinc sensing probes for prostate cancer. This work set the foundation for the research I completed during 2016/17 as part of an MSc by research in Biological Sciences. Through full time research branching across many disciplines, I developed a keen interest in the development of imaging probes and their transition from a chemistry-based environment to a biological one.
I am looking forward to starting the Medical Imaging CDT programme to improve the breadth and depth of my knowledge across the medical imaging field and to refine the skills I have developed throughout the years.

Project: Development of tracers for in vivo trafficking of essential trace metals in health and disease using PET imaging

I graduated from The University of Hull in 2016 with the degree of Master of Chemistry with Molecular Medicine with First Class Honours. During my degree I was part of two separate projects under Professor Steve Archibald and part of a third project during a summer placement. Each of these projects focused on a different aspect of PET imaging. By the halfway point of the first project, I had a keen interest in the field. When I was told about the CDT I realised it was an excellent opportunity to both develop and refine new skills whilst playing to the strengths I already have, as well as to broaden my understanding of the wider field of medical imaging in the multidisciplinary environment of the CDT.

Project: Novel Ga-68/67 complexes based on tris(hydroxypyridinone) (THP) conjugates for PET imaging and radionuclide therapy

I graduated from Polytechnic of Milan in 2016 with the degree of Master of Biomedical Engineering. Under the supervision of Professor Riccardo Vismara and Gianfranco Beniamino Fiore, I developed an interest in heart diseases and treatments. Until now, my research field has focused mainly on an experimental approach, but I hope to learn more about imaging techniques at the CDT. I am aiming to follow a career in biomedical engineering, so I am really excited to be given the opportunity to expand my research field with a clinical impact. Hopefully, thanks to the collaboration with St Thomas’ Hospital and to the possibility to work with professionals specialized in many different fields, I’ll be able to develop new skills and a better understanding of medical imaging.

Project: Simultaneous whole-heart coronary lumen/plaque and myocardial tissue characterization

I completed the MSc at the University of Padova (Italy) in Bioengineering, where I previously obtained the BSc in Information Engineering. During my Master, I have studied one year in Stockholm at the Royal Institute of Technology (KTH). I have done my Master’s thesis at the Cardiovascular Magnetic Resonance Research center at the Hospital of Lausanne (Switzerland). There I had the opportunity to get close to the world of medical imaging, in particular to MRI, and I would like to continue working and studying in this field. A PhD at this CDT is for me a great opportunity to receive a broad preparation on medical imaging from experts and specialists in the field.

Project: High-resolution whole-heart parameter mapping using image-based respiratory navigation and compressed sensing.

I graduated from the University of Birmingham in 2016, with a Master’s degree in Chemistry. There, I developed a keen interest in Nuclear Magnetic Resonance (NMR) spectroscopy and went on to use NMR in my final year project to characterise ionic liquid systems. The Centre for Doctoral Training (CDT) in Medical Imaging has allowed me to transfer my skills in NMR to Magnetic Resonance Imaging (MRI) and other medical imaging techniques. We are currently focused on developing gold nanoparticle-based MRI contrast agents capable of combined imaging and therapy of cancer. I use a clinical MRI scanner at St Thomas’ hospital to investigate the performance of our novel contrast agents and I use the tissue culture facility at Imperial College London to determine their uptake by and toxicity to different cell lines. I plan to study the therapeutic application of our contrast agents in the near future.

Project: Functionalised nanoparticles for theranostics

I graduated from Trinity College Dublin with a BA in Psychology and Imperial College London with an MSc in Computer Science. In between I worked at PLOS on some of their flagship journals. Prior to joining the CDT I’ve been a software engineer at Overleaf, a collaborate science writing platform for LaTeX.
I was inspired to join the CDT largely off the back of my masters research project using deep learning for medical imaging applications. I’m excited by the opportunity to work with interdisciplinary teams to further the possibilities of medical imaging.

Project: Comprehensive CRT CT imaging (3CI)

I completed my MSci in Chemistry at the University of Bristol in 2016, where I did my master’s project in the biofuels section of the Wass group. Investigating homogeneous ruthenium catalysts with phospinoamine chelators for the upgrade of synthesis gas to methanol strengthened my interest in coordination chemistry and for applying chemistry to real world problems. It fascinates me how small changes to ligands can tune the activity of a metal complex, and I look forward to synthesising new peptide-functionalised ligands for technetium-99m and rhenium-188 as part of my PhD project. I am excited to join the interdisciplinary research environment at St Thomas’ Hospital and to be given the opportunity to contribute to innovative medical imaging research. Oh, and I love playing Ultimate Frisbee.

Project: New platforms for 99mTc-labelled multimeric molecular SPECT imaging agents: bifunctional dithiocarbamate and diphosphine chelators

I acquired my BSc in Bioengineering and MSc in Biomedical Engineering in Portugal, at Faculty of Engineering, University of Porto. My undergraduate project, “Surface Tailoring for Selectively Control the Adhesion of Cells Relevant for Bone Tissue Engineering” was performed at 3B’s Research Group, University of Minho, my first interaction within a research environment. Further, during my masters, I had the opportunity to go to Barcelona (via Erasmus program) to do my Master thesis. There, I joined the Control of Stem Cell potency group where I wrote my thesis on “Development of a Decellularisation Protocol to Study the Role of Extracellular Matrix Proteins during Zebrafish Heart Regeneration”.
Since then, I have been really curious and fascinated about the heart tissue. My international experience, together with my academic training led to my interest in doing a PhD. Now, at KCL I am part of the British Heart Foundation (BHF) Centre of Research Excellence, where I am studying the possibility of using MRI as an imaging tool to access inflammation and extracellular matrix remodelling after a myocardial infarction.

Project: Molecular imaging of inflammation and extracellular matrix remodelling after Ml

I graduated with an MSci in Physics from Imperial College in 2016, before spending a year as a researcher in the department of medicine at the University of Manchester. During my final year at Imperial, I became interested in acoustics and fluid dynamics through studying the physics of ultrasound contrast agents (microbubbles).
I will build on my previous experience during my MRes/PhD project, in which I aim to develop new contrast ultrasound imaging techniques.

Project: High-resolution contrast-enhanced ultrasound elastography

I received my MSc in Natural Sciences (Physics) in 2013 from the University of Cambridge. My research interest is in the acquisition and reconstruction of medical imaging data.  The Centre for Doctoral Training provides a great environment to learn with support from both the academic staff and fellow PhD students.

Publications:
Spatially-Compact MR-Guided Kernel EM for PET Image Reconstruction
Authors: Bland, J., Belzunce, M. A., Ellis, S., McGinnity, C. J., Hammers, A. & Reader, A. J.
In : Transactions on Radiation and Plasma Medical Sciences, 2018
MR-Guided Kernel EM Reconstruction for Reduced Dose PET Imaging
Authors: Bland, J., Mehranian, A., Belzunce, M. A., Ellis, S., McGinnity, C. J., Hammers, A. & Reader, A. J.
In: Transactions on Radiation and Plasma Medical Sciences. PP, 99

Project: Sparse and synergistic multiparametric PET-MR image reconstruction for imaging brain disorders

During my BSc in Biomedical Sciences at King’s College London I specialised in Neuroscience and Pharmacology. Upon graduating I studied for an MRes in Clinical Drug Development at University College London where I conducted my research project in an medical imaging facility, The Centre for Advanced Biomedical Imaging. My project explored the feasibility of quantifying and assessing stroke severity in rodent models of focal ischemia using a novel preclinical, 1 tesla benchtop MRI system. Working on this project and in an interdisciplinary laboratory has led me to conducting a PhD in Medical Imaging on the CDT. I hope to develop significant skills in structural and functional image acquisition to better understand the complexity of brain function and the pathophysiology underlying neurological and psychiatric disorders.
jed.wingrove@kcl.ac.uk

Project: An imaging investigation of the central effects of insulin via intra-nasal administration

I graduated from Oxford University in 2015 with the degree of Master of Physics.   Following three months as an intern at the Institute of Cancer Research in London, under the supervision of Professor Gail ter Haar and Dr Ian Rivens, I developed an interest in ultrasound technology.  Excited by the technology’s non-invasive and non-ionising nature I hope to pursue this interest further at the CDT.  I am aiming to follow a career in medical physics and I am especially motivated by the opportunities within medical imaging to tackle research with a clinical impact.   I hope that the Centre’s interdisciplinary approach and association with the clinical environment of St Thomas’ Hospital will enable me to develop a comprehensive understanding of the field.

Publications

Acoustic Wave Sparsely-Activated Localization Microscopy (AWSALM): In Vivo Fast Ultrasound Super-Resolution Imaging using Nanodroplets

Zhang, G., Weinberg, P., Dunsby, C., Tang, M. X., Harput, S., Toulemonde, M., Broughton-Venner, J., Zhu, J., Riemer, K., Christensen-Jeffries, K., Brown, J. & Eckersley, R. J., 1 Oct 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. IEEE Computer Society, Vol. 2019-October. p. 1930-1933 4 p. 8926069

Activation and 3D Imaging of Phase-change Nanodroplet Contrast Agents with a 2D Ultrasound Probe

Harput, S., Zhang, G., Toulemonde, M., Zhu, J., Christensen-Jeffries, K., Brown, J., Eckersley, R. J., Dunsby, C. & Tang, M. X., 1 Oct 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. IEEE Computer Society, Vol. 2019-October. p. 2275-2278 4 p. 8925892

Minimization of Nanodroplet Activation Time using Focused-Pulses for Droplet-Based Ultrasound Super-Resolution Imaging

Zhang, G., Harput, S., Zhu, J., Christensen-Jeffries, K., Brown, J., Leow, C. H., Dunsby, C., Eckersley, R. J. & Tang, M. X., 1 Oct 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. IEEE Computer Society, Vol. 2019-October. p. 372-375 4 p. 8926067

Super-Resolution Ultrasound Image Filtering with Machine-Learning to Reduce the Localization Error

Harput, S., Grisan, E., Dunsby, C., Tang, M. X., Fong, L. H., Stanziola, A., Zhang, G., Toulemonde, M., Zhu, J., Christensen-Jeffries, K., Brown, J. & Eckersley, R. J., 1 Oct 2019, 2019 IEEE International Ultrasonics Symposium, IUS 2019. IEEE Computer Society, Vol. 2019-October. p. 2118-2121 4 p. 8925861

Cone beam computed tomography in Endodontics – a review of the literature

Patel, S., Brown, J., Pimentel, T., Kelly, R. D., Abella, F. & Durack, C., 1 Aug 2019, In : International Endodontic Journal. 52, 8, p. 1138-1152 15 p.

Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time

Christensen-Jeffries, K. M., Brown, J., Harput, S., Zhang, G., Zhu, J., Tang, M., Dunsby, C. & Eckersley, R., 1 Jul 2019, In : IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 66, 7, p. 1246-1254 9 p., 8717715.

3D Super-Resolution US Imaging of Rabbit Lymph Node Vasculature in Vivo by Using Microbubbles

Zhu, J., Rowland, E. M., Harput, S., Riemer, K., Leow, C. H., Clark, B., Cox, K., Lim, A., Christensen-Jeffries, K., Zhang, G., Brown, J., Dunsby, C., Eckersley, R. J., Weinberg, P. D. & Tang, M. X., 1 Jun 2019, In : Radiology. 291, 3, p. 642-650 9 p.

Fast acoustic wave sparsely activated localization microscopy: Ultrasound super-resolution using plane-wave activation of nanodroplets

Zhang, G., Harput, S., Hu, H., Christensen-Jeffries, K., Zhu, J., Brown, J., Leow, C. H., Eckersley, R. J., Dunsby, C. & Tang, M. X., 1 Jun 2019, In : IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 66, 6, p. 1039-1046 8 p., 8673629.

3-D Super-Resolution Ultrasound Imaging Using a 2-D Sparse Array with High Volumetric Imaging Rate

Harnut, S., Christensen-Jeffries, K., Brown, J., Zhu, J., Zhang, G., Leow, C. H., Toulemonde, M., Ramalli, A., Boni, E., Tortoli, P., Eckersley, R. J., Dunsby, C. & Tang, M. X., 17 Dec 2018, 2018 IEEE International Ultrasonics Symposium, IUS 2018. IEEE Computer Society, Vol. 2018-October. 8579662

3D in Vitro Ultrasound Super-Resolution Imaging Using a Clinical System

Christensen-Jeffries, K., Harput, S., Brown, J., Zhang, G., Zhu, J., Tang, M. X., Dunsby, C. & Eckersley, R., 17 Dec 2018, 2018 IEEE International Ultrasonics Symposium, IUS 2018. IEEE Computer Society, Vol. 2018-October. 8580144

Development of Simultaneous Optical Imaging and Super-Resolution Ultrasound to Improve Microbubble Localization Accuracy

Brown, J., Kolas, S., Christensen-Jeffries, K., De Menezes, C., Harput, S., Zhu, J., Zhang, G., Tang, M. X., Dunsby, C. & Eckersley, R. J., 17 Dec 2018, 2018 IEEE International Ultrasonics Symposium, IUS 2018. IEEE Computer Society, Vol. 2018-October. 8580212

Fast Acoustic Wave Sparsely Activated Localization Microscopy (Fast-AWSALM) Using Octafluoropropane N Anodroplets

Zhang, G., Harput, S., Hu, H., Christensen-Jeffries, K., Zhu, J., Brown, J., Leow, C. H., Dunsby, C., Eckersley, R. J. & Tang, M. X., 17 Dec 2018, 2018 IEEE International Ultrasonics Symposium, IUS 2018. IEEE Computer Society, Vol. 2018-October. 8580192

Acoustic wave sparsely activated localization microscopy (AWSALM): Super-resolution ultrasound imaging using acoustic activation and deactivation of nanodroplets

Zhang, G., Harput, S., Lin, S., Christensen-Jeffries, K., Leow, C. H., Brown, J., Dunsby, C., Eckersley, R. J. & Tang, M. X., 2 Jul 2018, In : APPLIED PHYSICS LETTERS. 113, 1, 014101.

Two-stage Motion Correction for Super-Resolution Ultrasound Imaging in Human Lower Limb

Harput, S., Christensen-Jeffries, K., Brown, J., Li, Y., Williams, K. J., Davies, A. H., Eckersley, R. J., Dunsby, C. & Tang, M. X., 7 Apr 2018, In : IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

3-D Motion Correction for Volumetric Super-Resolution Ultrasound Imaging

Harput, S., Christensen-Jeffries, K., Brown, J., Zhu, J., Zhang, G., Eckcrslcy, R. J., Dunsby, C. & Tang, M. X., 1 Jan 2018, In : IEEE International Ultrasonics Symposium, IUS. 2018-January, 8580145.

Ultrasound super-resolution with microbubble contrast agents

Harput, S., Christensen-Jeffries, K., Brown, J., Eckersley, R. J., Dunsby, C. & Tang, M. X., 25 Dec 2017, IEEE SENSORS 2017 – Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., Vol. 2017-December. 3 p.

Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Christensen-Jeffries, K., Harput, S., Brown, J., Wells, P. N. T., Aljabar, P., Dunsby, C., Tang, M. X. & Eckersley, R. J., Nov 2017, In : IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL. 64, 11, p. 1644-1654

Automated super-resolution image processing in ultrasound using machine learning

Jeffries, K. C., Schirmer, M., Brown, J., Harput, S., Tang, M. X., Dunsby, C., Aljabar, P. & Eckersley, R., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society Press, 8091563

Investigation of microbubble detection methods for super-resolution imaging of microvasculature

Brown, J., Christensen-Jeffries, K., Harput, S., Dunsby, C., Tang, M. X. & Eckersley, R. J., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society, 8092177

Localisation of multiple non-isolated microbubbles with frequency decomposition in super-resolution imaging

Harput, S., Christensen-Jeffries, K., Brown, J., Eckersley, R. J., Dunsby, C. & Tang, M. X., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society, 8091727

Microbubble localization errors in ultrasonic super-resolution imaging

Jeffries, K. C., Harput, S., Brown, J., Dunsby, C., Aljabar, P., Tang, M. X. & Eckersley, R., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society Press, 8091846

Super-resolution ultrasound to aid testicular lesion characterisation

Jeffries, K., Huang, D. Y., Brown, J., Harput, S., Dunsby, C., Tang, M. X., Sidhu, P. S. & Eckersley, R., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society, 8091568

Two Stage Sub-Wavelength Motion Correction in Human Microvasculature for CEUS Imaging

Harput, S., Christensen-Jeffries, K., Li, Y., Brown, J., Eckersley, R. J., Dunsby, C. & Tang, M. X., 31 Oct 2017, 2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society Press, 8091703

‘Non-standard’ panoramic programmes and the unusual artefacts they produce

Harvey, S., Ball, F., Brown, J. & Thomas, B., 25 Aug 2017, In : British Dental Journal. 223, 4, p. 248-252 5 p.

3-D In Vitro Acoustic Super-Resolution and Super-Resolved Velocity Mapping Using Microbubbles

Christensen-Jeffries, K., Brown, J., Aljabar, P., Tang, M., Dunsby, C. & Eckersley, R., 31 Jul 2017, In : IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL. 64, 10, p. 1478-1486

 

Project: Super-resolution ultrasound imaging

I previously completed my undergraduate degree in Chemistry at the University of York. I have five years industrial experience in R&D working for the chemical company AkzoNobel. My research interests include development of novel PET tracers and MR contrast agents and I am excited to see the impact of the introduction of clinical PET-MR to the field. After completing my PhD I hope to continue my industrial career within a company that specialises in medical imaging.

Project: Bifunctional chelator design for rapid in vitro and in vivo labelling of targeting biomolecules with short half life radiometals

With my MSc in Neuroscience at ETH Zürich I had the chance to approach the world of Medical Imaging from two main perspectives. During that period, in fact, I was involved in projects that focused on both the investigation of the neurobiological basis of brain functioning, and the study of its modulations via computational models. Thanks to the great interdisciplinarity of the EPSRC Centre for Doctoral Training in Medical Imaging and its close collaboration with the industry, I hope to enlarge that vision and take part in cutting edge research.

Publications

An automated machine learning approach to predict brain age from cortical anatomical measures
Dafflon, J., Pinaya WHL, Turkheimer F,et al., May 2020, In: Human Brain Mapping. 2020, p. 1–12.

Conflicting Emergences. Weak vs. strong emergence for the modelling of brain function
Turkheimer, F. E., Hellyer, P., Kehagia, A. A., Expert, P., Lord, L-D., Vohryzek, J., De Faria Dafflon, J., Brammer, M. & Leech, R., Apr 2019, In : Neuroscience and Biobehavioral Reviews. 99, p. 3-10 8 p.

Project: Biologically interpretable models for brain disorders

After studying Aeronautical Engineering (MEng) at Imperial College London, I joined the Computational Modelling stream within the CDT. I am currently on my 3rd year as a PhD student, focusing on the non-invasive estimation of clinically relevant cardiovascular metrics, such as blood pressure or arterial stiffness. I combine medical imaging data and peripheral pressure measurements with fast computational methods to obtain estimates of central (aortic) waveforms and indices.

Publications

Modeling arterial pulse waves in healthy aging: a database for in silico evaluation of hemodynamics and pulse wave indexes
Charlton, P. H., Mariscal Harana, J., Vennin, S. M. L., Li, Y., Chowienczyk, P. J. & Alastruey-Arimon, J., 1 Nov 2019, In : American Journal of Physiology (Heart and Circulatory Physiology). 317, 5, p. H1062-H1085 24 p.

Simulated Arterial Pulse Waves Database (preliminary version)
Charlton, P. H., Mariscal Harana, J., Vennin, S. M. L., Chowienczyk, P. J. & Alastruey-Arimon, J., 10 Jul 2019

Pulse Wave Database (PWDB): A database of arterial pulse waves representative of healthy adults
Charlton, P. H., Mariscal Harana, J., Vennin, S. M. L., Li, Y., Chowienczyk, P. J. & Alastruey-Arimon, J., 10 Apr 2019

An assessment of algorithms to estimate central blood pressure from non-invasive measurements
Mariscal Harana, J., Charlton, P. H., Sherwin, S. J. & Alastruey-Arimon, J., 2019, Computational & Mathematical Biomedical Engineering 2019 Proceedings. Vol. 2. p. 603-606 4 p. (CMBE Proceedings).

Optimization of topological complexity for one-dimensional arterial blood flow models
Fossan, F. E., Mariscal-Harana, J., Alastruey, J. & Hellevik, L. R., 12 Dec 2018, In : Journal of the Royal Society Interface. 15, 149, 20180546.

A Study on the Characteristics Influencing the Pressure at the Root of a Distributed One-Dimensional Model of Arterial Blood Flow
Abdullateef, S., Harana, J. M., Alastruey, J. & Khir, A. W., 2018, Computing in Cardiology, CinC 2018, Maastricht, The Netherlands, September 23-26, 2018.

An Integrated Software Application for Non-invasive Assessment of Local Aortic Haemodynamic Parameters: 20th Conference on Medical Image Understanding and Analysis (MIUA 2016)
Florkow, M., Mariscal Harana, J., van Engelen, A., Rafiq, I., de Bliek, H., Schneider, T., Alastruey-Arimon, J. & Botnar, R. M., 2016, In : Procedia Computer Science. 90, p. 2-8 7 p.

Project: Non-invasive proximal blood pressure estimation by combining MR imaging with one-dimensional flow modelling

I recently graduated from Imperial College London with an MSci in Chemistry. During my Master’s project I successfully worked to develop some model reactions for Carbon-11 radiolabelling for PET imaging purposes. This project served as a good introduction to the field of medical imaging and with this CDT I look forward to further work in this important field. My main interests are in PET tracer synthesis, and the development of new synthetic methods. I hope that during my PhD I will be able to develop both my skills as a chemist and also as a researcher involved in a truly interdisciplinary area of study.

Publications
In-loop flow [11C]CO2 fixation and radiosynthesis of N,N′-[11C]dibenzylurea
Downey, J., Bongarzone, S., Hader, S. & Gee, A. D., 22 Dec 2017, In : JOURNAL OF LABELLED COMPOUNDS & RADIOPHARMACEUTICALS.

Project: New routes to carbon-11 based molecular imaging agents for in vivo PET imaging

I studied physics at Pontifical Catholic University of Chile where I did 2 years of research in bio-nanotechnology. After I got my master’s degree in Medical Physics at King’s College London I went back to Chile to work in PET & Radionuclide production. During doctoral training I intend to deepen my knowledge in magnetic resonance imaging as well as to further develop my independent work skills and to explore entrepreneurial ideas in medical technology. My main research interests are in image acquisition, analysis and fusion of different imaging modalities.
Publications

Contrast-free high-resolution 3D magnetization transfer imaging for simultaneous myocardial scar and cardiac vein visualization.
López, K., Neji, R., Mukherjee, R.K. et al., In: Magn Reson Mater Phy (2020).

Non‐contrast enhanced simultaneous 3D whole‐heart bright‐blood pulmonary veins visualization and black‐blood quantification of atrial wall thickness
Ginami, G, López, K, Mukherjee, RK, et al., In:  Magn Reson Med. 2019; 81: 1066– 1079.

High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI: HD-PROST reconstruction for accelerated multi-contrast MRI
Bustin, A., Cruz, G., Jaubert, O., Lopez Gonzalez, K., Botnar, R. & Prieto, C., 4 Mar 2019, In : Magnetic Resonance in Medicine. 81, 6, p. 3705-3719 15 p.

Project: Tissue characterisation for the management of cardiac arrhythmia

I graduated from the University of Manchester with the MPhys in Theoretical Physics degree. My first interest in health related science developed at the Met Office, where I had the summer internship in the health team. In the Met office I worked on the method for forecasting of the spores releases and their effect on people with asthma and allergy.  During final year of my studies I completed a master’s thesis in the field of medical imaging while I was working on the method of automated digital mammography analysis.

Project: Computational modelling of dynamic brain connecting networks for disease prediction

I am an Electrical and Computer Engineer (MEng) from Greece with research and development experience in the field of machine learning and image processing. Working as an R&D engineer for 2 years during my studies and as a research assistant at Information Technologies Institute (in Thessaloniki, Greece) for 2 years after my graduation, I have completed emotion recognition, action recognition and fire recognition projects.
My keen interest in neuroimaging and my desire to turn to machine learning applications to neuroimaging and medical imaging in general, led me to the CDT programme. CDT is for me the next adventure in the world of research and I believe it would be a highly challenging but equally fascinating one.

Project: Addressing the brain correspondence problem: predicting robust and accurate mappings between multi-modal feature sets through use of deep learning

I am a MPhil/PhD student in Biomedical Engineering & Imaging Sciences at King’s College London. I studied Physics at the Università di Padova (Italy) and finished my master studies in September 2017. I developed my master thesis at the GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt (Germany), at the department of Biophysics, in the field of radiobiological modelling. I am currently a member of the HYBRID consortium and in particular I am working on simultaneous PET/MRI image analysis.

During my year abroad, I was lucky enough to work in the Orvig group at UBC Vancouver. Professor Orvig specialises in Medicinal Inorganic Chemistry, and his depth and range of knowledge inspired me to pursue my interest in this area. I have also performed polymer research (Manners group) and bio-nanomaterial engineering (Davis/Mann group) at the University of Bristol, where I obtained my MSci degree in Chemistry. I’m excited to learn more about multimodality imaging and gain hands-on experience of medical imaging from bench to bedside.

Project: Innovative multimodality short and long term in vivo cell tracking platform for cellular therapy applications

My name is Marco Fiorito and I come from Italy, where I got my BSc and MSc in Physics at the University of Turin, including a brief parenthesis at the Technical University of Eindhoven. At the end of my studies I was looking for an academic position that would allow me to further develop the skills I had acquired and the EPSRC CDT program offered by King’s College London felt like the ideal continuation. Here I have worked on the mathematical modelling and experimental validation, through magnetic resonance elastography, of the signature shift in tangent stiffness generated by a pressurised tumour onto the surround soft tissue and its detection using shear waves. This project allowed me to gain an expertise in several fields, developed through the constant facing of different experimental and computational challenges, and helped me grow as a scientist and as a person. This was also possible thanks to the helpful and supportive people I had the chance to share the lab and office space with. Right now I am about to finish my thesis and to embark on a new experience at the University of Basel and I am confident that this PhD is going to open many more doors in my future.

fiorito.marco@kcl.ac.uk

Project: Imaging therapy for cancer treatment: strain-induced cell death via MRI focused shear waves

I graduated in 2015 at the University of Trento in 2015 with a degree of Master of Mathematics. In the course of my master’s second year, I got interested in biomedical field and I began my research thesis attending an internship with Professor E. F. Toro to deepen my knowledge on numerical simulation of the human cardiovascular system. During this training of several months, I further developed my interest in medicine, realizing that computational modelling can have a significant role in medical analysis and treatment. The Centre for Doctoral Training offers high-level courses, and the possibility to be a part of a stimulating environment as St Thomas’ Hospital. I hope that my PhD at the CDT will provide me the knowledge that I need to continue my academic career in the biomedical field.

Project: Towards understanding 4-chamber pressures in heart failure and resynchronization

I read Chemistry (MChem) at the University of Oxford, Brasenose College. During my Master’s thesis I developed a high-throughput screening technique for oxygen sensing enzymes. I now have the opportunity to branch out into a very innovative field of medical sciences. My main interest is in applying chemistry to design advanced probes for medical imaging. By the end of my PhD I hope to have acquired both critical and creative thinking and be equipped with a large portfolio of laboratory techniques.
marta.dazzi@kcl.ac.uk

Project: Imaging anatomical variation in uptake of plasma macromolecules by the coronary artery wall

In 2017 I graduated from Newcastle University with a BSc honours degree in Chemistry. Throughout my undergraduate studies, I undertook several research projects under the joint supervision of Dr Lee Higham, and Dr Andrew Pike. Whilst conducting my research, I became fascinated with medical imaging, specifically the design and synthesis of radiopharmaceuticals for use as imaging probes. During my final year, I wrote a literature review entitled ‘The Role of 99mTc in Medical Imaging’.
Whilst at the CDT I hope to make the most of the resources available, as well as the knowledge and experience of its staff and my fellow students alike.

Project: Increasing radioactive payload at peptide receptors in diseased tissue: bifunctional dendritic chelators for complexing radioactive metal ions

In 2016 I graduated from King’s College London with a BEng in Biomedical Engineering. Following several projects under the supervision of Dr. David Nordsletten, I developed a keen interest in the field of numerical modelling and its use in the understanding of the biomechanics of the heart. I look forward to joining the CDT, particularly due to the work carried out at the department at King’s on the personalization of cardiac computational models and their translation to clinical applications. I hope that during my PhD I will gain the necessary skills to pursue a career in this emerging field of research.

Project: Computational analysis of chronotropic modulation in the congenital heart

I completed my BSc in Theoretical Physics at the University of Birmingham before moving to Imperial College London to earn my MSc in Applied Mathematics. During both my previous degrees I took great interest in the use of mathematics in contexts less ‘obvious’ than the physical sciences, particularly through the use of numerical models and computers. My dissertation focused on quantitative sociodynamics, and whilst I enjoyed the research, I realised I ultimately wanted to pursue further study in a field with more potential for real world application. The CDT in Smart Medical Imaging was a perfect fit for me, combining my interest in physics, mathematics and computing into a field of research with the very real possibility of positively affecting people’s lives.

Project: Deep-learning PET-MR longitudinal reconstruction for lower-dose antibody-imaging in the understanding and treatment of cancer

I graduated with an MSci in Chemistry from Imperial College London in June 2016. In my final year I worked on a project synthesising dual modal imaging probes using upconversion nanoparticles. The work sparked my interest in the area of medical imaging, specifically synthesising nanoparticle probes for biomedical imaging. My MSci project gave me a taste of the field and I had opportunity to collaborate with researchers, both in the Physics department at Imperial College London and researchers working at Hong Kong Baptist University. I’m looking forward to continued collaboration during my time at the EPSRC Centre for Doctoral Training.

Project: Novel nanoscopic multimodal imaging agents and their applications – Optical, CT, PET/SPECT and MRI active nanoparticles

I graduated from Centrale Paris Engineer School in 2014 with the degree of Engineer in Aeronautics and Space. Following a six month internship in image processing for the conception of reactor blades in Bordeaux , I started working as an engineer on GE’s PET/MR System at the Neuroimaging facility CENIR, under the supervision of Professor Stéphane Lehéricy, where I developed an interest for the MR technology.  Impressed by the variety and complexity of MR acquisition I hope to deepen my knowledge of MR Physics, acquisition and reconstruction with the CDT. I am aiming for a career in medical imaging and I am especially motivated by the opportunities to tackle challenging research with a clinical impact. I hope that I will be able to contribute to the Centre’s interdisciplinary approach and help in association with the clinical environment of St Thomas’ Hospital to improve the existing methods of MR acquisition.

Publications

Free-running Cardiac Magnetic Resonance Fingerprinting: Joint T1/T2 map and CINE imaging
Jaubert, O. F., Lima da Cruz, G. J., Bustin, A., Schneider, T., Koken, P., Doneva, M., Rueckert, D., Botnar, R. M. & Prieto Vasquez, C., 1 May 2020, In : Magnetic resonance imaging. 68, p. 173-182 10 p., MRI_9383.

Multi-parametric liver tissue characterization using MR Fingerprinting: simultaneous T1, T2, T2* and fat fraction mapping
Jaubert, O., Arrieta, C., Lima da Cruz, G., Bustin, A., Schneider, T., Georgiopoulos, G., Masci, P-G., Sing-Long, C., Botnar, R. & Prieto Vasquez, C., 16 Apr 2020, (Accepted/In press) In : Magnetic Resonance in Medicine. mrm.28311.

Isotropic 3D Cartesian single breath-hold CINE MRI with multi-bin patch-based low-rank reconstruction
Kustner, T., Bustin, A., Jaubert, O., Hajhosseiny, R., Masci, P-G., Neji, R., Botnar, R. & Prieto Vasquez, C., 9 Mar 2020, (Accepted/In press) In : Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine.

Free-running simultaneous myocardial T1/T2 mapping and cine imaging with 3D whole-heart coverage and isotropic spatial resolution
Qi, H., Bustin, A., Cruz, G., Jaubert, O., Chen, H., Botnar, R. M. & Prieto, C., 1 Nov 2019, In : Magnetic resonance imaging. 63, p. 159-169 11 p.

3D Cartesian Fast Interrupted Steady-State (FISS) Imaging
Kustner, T. M. C., Bustin, A., Jaubert, O. F., Neji, R., Prieto Vasquez, C. & Botnar, R. M., Nov 2019, In : Magnetic Resonance in Medicine. 82, 5, p. 1617-1630 14 p.

Water/fat Dixon Cardiac Magnetic Resonance Fingerprinting
Jaubert, O. F., Lima da Cruz, G. J., Bustin, A., Schneider, T., Lavin, B., Koken, P., Hajhosseiny, R., Doneva, M., Rueckert, D., Botnar, R. M. & Prieto Vasquez, C., 17 Oct 2019, (Accepted/In press) In : Magnetic Resonance in Medicine.

Free-running 3D Whole Heart Myocardial T1 Mapping with Isotropic Spatial Resolution
Qi, H., Jaubert, O., Bustin, A., Cruz, G., Chen, H., Botnar, R. & Prieto, C., 1 Oct 2019, In : Magnetic Resonance in Medicine. 82, 4, p. 1331-1342 12 p.

High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI: HD-PROST reconstruction for accelerated multi-contrast MRI
Bustin, A., Cruz, G., Jaubert, O., Lopez Gonzalez, K., Botnar, R. & Prieto, C., 4 Mar 2019, In : Magnetic Resonance in Medicine. 81, 6, p. 3705-3719 15 p.

Sparsity and Locally Low Rank Regularization for Magnetic Resonance Fingerprinting
Lima da Cruz, G. J., Bustin, A., Jaubert, O. F., Schneider, T., Botnar, R. M. & Prieto Vasquez, C., 29 Dec 2018, (Accepted/In press) In : Magnetic Resonance in Medicine.

Rigid Motion Corrected Magnetic Resonance Fingerprinting
Lima da Cruz, G. J., Jaubert, O. F., Schneider, T., Botnar, R. M. & Prieto Vasquez, C., 3 Sep 2018, In : Magnetic Resonance in Medicine.

Project: Cardiac multiparametric magnetic resonance fingerprinting

I gained my M.Sc. in Electrical Engineering and Information Technology from the Karlsruhe Institute of Technology, Germany. During my master studies, I majored in signal processing and became particularly interested in medical applications. For my final thesis, I developed an image-based approach for tracking laparoscopic instruments during surgery in real-time.

Project: iDWI: a novel approach to diffusion-weighted imaging in MRI

I recently completed an integrated Master’s course in Chemistry at Cardiff University. My final year project involved the development of functionalised iron oxide nanoparticles for dual modality MRI and PET imaging. This sparked an interest in medical imaging and in particular, the chemistry involved in the formulation of medical imaging probes. I hope to further my understanding of this area of research throughout my years as a PhD student.
patrick.bergstrom_mann@kcl.ac.uk
 

Project: The use of bisphosphonates as phase transfer reagents for bioactive fluorescence and near-infrared emitting quantum dots

I have an interest in using computational models derived from biophysical measures to study the complexity of the brain in terms of function and neuroanatomy. I am fascinated by the complexity of the human mind and by how neuroscience is transforming our understanding of what constitutes mental illness and the separation between the healthy and the abnormal brain.
I specialise in diffusion MRI tractography, a neuroimaging modality that allow us, to explore non-invasively, the trajectories of white matter axons in the living human brain.  Like other neuroimaging techniques, diffusion MRI can provide us with large amounts of biophysical data that have the potential to reveal insightful information about the brain.
Nevertheless, this rich data will yield optimal results only when the best possible methods of analysis are also applied. An example of this is the data collected from hundredths of MRI scans on healthy individuals for the Biomedical Research Centre (BRC) project for a MRI atlas of the brain. Within my PhD project I am developing and applying such methods to data already collected by the BRC and by other studies at the IoPPN.
Qualifications and History
MSc Mathematics, University of Granada, Spain
MSc Neuroimaging, King’s College London
Research:
New strategies for group comparison and automatic analysis of large-scale tractography datasets
Over the years, several diffusion Magnetic Resonance Imaging (MRI) and tractography techniques have been developed for the study of the brain. With diffusion MRI and tractography we can investigate the microstructure properties of tissue and make inferences about structure connectivity between local or more distant regions in the brain.
Most tractography methods generate large amounts of data in the form of millions of “streamlines” representing the pathways of plausible neurite connections in the brain. Because of its size and complexity, tractography data remains difficult to analyse. For example, to obtain accurate anatomical reconstructions this data usually has to be segmented using dedicated and time consuming manual methods like virtual “dissections”, as automatic tract-segmentation procedures do not provide yet optimal results. Therefore, the quantification and analysis of tractography datasets becomes a difficult task or a time-consuming process that is not easily translated to large studies.
Nevertheless, the information conveyed by tractography data expands that available through other neuroimaging modalities increasing our capacity to detect and to interpret differences between groups of subjects in neuroimaging studies.
In my PhD project, I study existing and emerging approaches for the group-level analysis of diffusion MRI tractography data. I identify and implement potential new metrics and methods for tractography analysis and then, I evaluate their application in the context of group studies.
Pedro is funded by the Maudsley NIHR BRC
 

I received my MChem from the University of Hull in 2015 where I spent my masters project and several summer projects working on medical imaging based research. Hence, the CDT was a natural next step for me to take. Over the last few years as part of the CDT, I have learnt an abundance of new skills; from radiochemistry to testing my compounds in animals.
Publications
PET Imaging of Liposomal Glucocorticoids using 89Zr-oxine: Theranostic Applications in Inflammatory Arthritis
Gawne, P. J., Clarke, F., Turjeman, K., Cope, A. P., Long, N. J., Barenholz, Y., Terry, S. Y. A. & T. M. de Rosales, R., May 2020, In : Theranostics. 10, 9, p. 3867-3879
Nuclear Imaging of Liposomal Drug Delivery Systems: A Critical Review of Radiolabelling Methods and Applications in Nanomedicine
Man, F. A. W. M., Gawne, P. J. & T. M. de Rosales, R., 2019, In : ADVANCED DRUG DELIVERY REVIEWS. 143, p. 134-160 27 p.
Synthesis, gallium-68 radiolabelling and biological evaluation of a series of triarylphosphonium-functionalized DO3A chelators
Smith, A. J., Gawne, P. J., Ma, M. T., Blower, P. J., Southworth, R. & Long, N. J., 17 Oct 2018, In : Dalton transactions (Cambridge, England : 2003).
Manganese-52: Applications in Cell Radiolabelling and Liposomal Nanomedicine PET Imaging using Oxine (8-hydroxyquinoline) as an Ionophore
Gawne, P. J., Man, F. A. W. M., Fonslet, J., Radia, R., Bordoloi, J. K., Cleveland, M., Jimenez-Royo, P., Gabizon, A., Blower, P. J., Long, N. & T. M. de Rosales, R., 2018, In : Dalton Transactions. 47, 28, p. 9283-9293 10 p.
 

Project: Cell and liposome tracking by PET with zirconium-89

I graduated from University College London with an MSci in Natural Sciences majoring in Organic Chemistry and a minor in Biomedical Sciences. My Master’s project aimed to see whether induced Advanced Glycation Endproducts could be characterised via optical (Raman and fluorescence) spectroscopy. My main interest is how we can chemically construct the next generation of theranostic probes in targeting cancer. This CDT programme is an exceptional opportunity to work in an exciting field at the interface of biomedicine and engineering. By the end of the PhD I hope to incorporate an arsenal of laboratory techniques, knowledge and imagination to help advance the field of Medical Imaging.

Project: Novel theranostic targeted anti-cancer probe for multi-modal imaging on multiple scales

I received my MChem in Chemistry (with Medicinal and Biological Chemistry) from the University of York in 2015, having undertaken my Master’s project in the Oivanen Organic Chemistry group at the University of Helsinki. My research interest is primarily in the application of chemistry to improving the quality of life and medical care available, and I am excited to explore the potential of medical imaging technologies in benefiting humanity. Being a part of the CDT in Medical Imaging is a fantastic opportunity to obtain skills and knowledge, and work in a multi-disciplinary environment to pool ideas and resources to better tackle potential research questions.

Project: Developing new targeted molecular contrast agents for imaging inflammation of vulnerable plaques

I graduated with an integrated Masters in Physics from The University of Manchester in 2009. My MPhys project was supervised by Dr Oleg Aslanidi who later joined the Division of Imaging Sciences and Biomedical Engineering at King’s College, London (KCL). The project involved the mathematical modelling of electrophysiological processes in cardiomyocytes to investigate atrial fibrillation and was published as an IEEE conference paper. I enjoyed doing the computational research, but had always felt compelled to share my expertise through teaching. After completing my PGCE and teaching for 5 years, I suffered a cardiac arrest – I had just turned 27 years old. I had a defibrillator implanted (called Danny) and I spent 6 months recovering and reconsidering my career. The coincidence between my MPhys research and my own life made me get in contact with Dr. Aslanidi for advice about getting back into academia and pursuing a research career. I joined the stand-alone Master of Research (MRes) course in Medical Imaging Sciences at KCL where I also met the cohort of students starting out in the new Centre for Doctoral Training (CDT) in Medical Imaging.

Project: Automated quality control and semantic parsing in multi-modal imaging

Software engineer with a strong interest in deep learning and its application in medicine. I finished my Master’s degree in electrical engineering and information technology at the Karlsruhe Institute of Technology (KIT) in Germany where I specialised in deep learning and biomedical engineering. During my studies I worked as a research assistant and intern on finite element simulations of the heart, CT image denoising, autonomous driving, and GAN-based face manipulation. Other than that, I love football, training AIs and VIM.

Project: Explainable AI for diagnosing and treating cardiovascular disease

Following my undergraduate MPhys degree in physics at the University of Surrey, I came to the KCL/Imperial CDT in Medical Imaging in 2014 to study for my PhD. During this period, I worked on my thesis entitled ‘Multi-Dataset Image Reconstruction for Longitudinal and Multi-Tracer Positron Emission Tomography’, supervised by Professor Andrew Reader and Professor Julia Schnabel. The aim of the project was to investigate novel image reconstruction methods that allow the transfer of information between PET datasets acquired for the same patient at multiple times (for instance, to monitor treatment response) or multi-tracer PET datasets (typically used to obtain complementary information about a specific biological process). By encouraging this transfer of information between the images during the image reconstruction process, we aimed to reduce image noise, thereby improving the quality of the resulting images. The results of our experiments showed that these novel methods can be used to improve image quality in longitudinal oncology treatment monitoring PET imaging and in multi-tracer brain PET. I am currently working on a short-term post-doc with Professor Reader, investigating novel methods of performing regularised PET image reconstruction.

Project: Multi-dataset PET/MR direct parametric image reconstruction for longitudinal studies and atlas building

I obtained a dual MSc in electrical engineering from the Ecole Nationale Supérieure de l’Electronique et ses Applications, Cergy, France, and in biomedical engineering from Imperial College London. My master thesis, focused on microvascular palpation using micro bubbles and ultrasound, made me realise I wanted to pursue a career in research in the exciting field of bioengineering and I am currently completing a PhD in cardiovascular medicine at King’s British Heart Foundation Centre. Due to the interdisciplinary nature of my project, I am based at King’s Imaging Division and I am grateful to the CDT for providing me with the opportunities to enhance my PhD experience, as well as broadening my knowledge on healthcare-related topics.

I graduated from Imperial College London with an MEng in electrical and electronic engineering and after working for a couple of months decided that I wanted to go back to university to pursue a PhD. My interests are signal processing and data classification in a medical context, so during my PhD I’m hoping to learn a lot about these subjects.

Publications:
Multiband RF pulse design for realistic gradient performance
Authors: Abo Seada, S., Price, A. N., Schneider, T., Hajnal, J. V. & Malik, S. J.
In: Magnetic Resonance in Medicine, 2018, DOI: 10.1002/mrm.27411
Optimized amplitude modulated multiband RF pulse design
Authors: Abo Seada, S.; Price, A.N.; Hajnal, J.V.; Malik, S.J.
In: Magnetic Resonance in Medicine, 2017, DOI: 10.1002/mrm.26610

Project: Rebalancing MRI encoding schemes – an exploration of combined transmit and receive parallel imaging approaches

I completed my undergraduate degree in Physics at Queen’s University Belfast. In my penultimate year as an undergraduate, I took some modules in medical physics, and became interested in pursuing a career in this field. To this end, I applied for the NHS Scientist training programme, specialising in Medical Physics. My application was successful and I began the 3-year training programme at King’s College Hospital, London in September 2013. This involved a short placement in each of the four areas of medical physics, followed by a long placement in my chosen specialism (MRI and Ultrasound), alongside completing an MSc in Medical physics. The research topic of my MSc thesis was T1 mapping in the myocardium. I found this area of research interesting and rewarding, and this ultimately lead to my decision to join the CDT programme in July 2018. My research is focused on developing cardiac perfusion MRI, using advanced techniques such as simultaneous multi-slice MRI.

Project: Advanced cardiac magnetic resonance perfusion imaging

I have recently completed my MChem studies at the University of Oxford. My final year research project, under the supervision of Professor Stephen Faulkner, focused on the synthesis and halide binding properties of luminescent lanthanide complexes. This research led me to my current interest in the design and synthesis of ligand species for use in metal-based imaging probes. I hope that the Medical Imaging CDT programme will allow me to expand my knowledge and skills in this field alongside offering new insight into the multidisciplinary area of imaging sciences on the whole, both within the laboratory and beyond.

Project: Simplification of radiopharmaceutical formulation through structural modification: comparing multidentate ligand topologies for new 99mTc and 188Re imaging agents