Smart Medical Imaging

EPSRC Centre for Doctoral Training


Current Projects

  • Jennifer Young

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

    Jennifer Young - 2014 entry

    The advent an imminent marketing authorisation of the gallium-68 generator presents great scope for development of applications of this short half life isotope in PET imaging. Fast,simple methods to incorporate short half life radiometals such as Ga-68 and Bi-213 into radiopharmaceuticals are required to facilitate clinical application on a wide scale - labelling must be quick and simple, under mild conditions and yielding high specific activity with extremely low amounts of biomolecules (eg 10 microgram). This is a challenge for chelator design, because features of chelators that promote in vivo kinetic stability (required to ensure that the biomolecule keeps its label in vivo for long enough to perform the scan), such as macrocyclic structure, impose high kinetic barriers to labelling making labelling slow or requiring harsh conditions. More...

  • Adela Capilnasiu

    Fighting fibrosis: a complementary biomechanical approach to characterize and distinguish fibrosis from inflammation in chronic diseases of the liver and heart

    Adela Capilnasiu - 2014 entry

    Aim of this PhD project is: 1. to develop a comprehensive package for the assessment of biomechanical information (MR-elastography sequence development and reconstruction of biomechanical information using non-linear elasticity and finite element techniques), 2. to perform clinical studies on patients with liver fibrosis/inflammation and heart diseases (in particular patients with normal ejection fraction), and 3. to correlate the biomechanical information to detailed histology, molecular profiles, and PET-MR metrics. More...

  • Giovanna Nordio

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

    Giovanna Nordio - 2014 entry

    To develop image-based respiratory motion corrected parameter mapping in conjunction with compressed sensing image acceleration methods. This will enable the use of motion corrected whole-heart T1 and T2 mapping with high spatial resolution in a clinically feasible scan time. Such parameter mapping techniques may be clinically valuable tools for the detection of myocardial fibrosis and oedema as well as for coronary plaque characterization. More...

  • Marta Dazzi
  • Marco Fiorito

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

    Marco Fiorito - 2014 entry

    We propose to investigate a novel pathway to induce cell death non-invasively for cancer treatment in vitro and in vivo. We plan to induce programmed cell death (apoptosis) via focussed shear waves operating at specific frequencies and amplitudes. Our preliminary work in vitro showed that apoptosis can be triggered via mechanical shear “excitation” acting on cell surface adhesion receptors. Now, we plan to build on this data and investigate the frequency/amplitude wave spaces suitable to induce cancer cell death in vivo and how such mechanical ‘stimulation’ is translated into specific biochemical signals. Subsequently, we will employ pre-clinical murine models of human solid cancers and subject tumours to shear excitation. Using a 3T PET-MR system, apoptosis will be assessed in-vivo via ICMT11 (PET) and tumour viability via diffusion and perfusion MRI. More...

  • Christopher Bowles

    Machine Learning for Differential Diagnosis of Dementia from multi-modality MR and PET imaging

    Christopher Bowles - 2014 entry

    The aim of the PhD project is to investigate the potential of machine learning and multi-modality MR imaging and PET for differential diagnosis of dementias. The project has the following objectives: 1. To identify features from MR and PET images that can be used for differential diagnosis and early detection of dementia. 2. To develop machine learning techniques that allow the classification of subjects into different categories of dementia. 3. To implement and evaluate a decision support tool for differential diagnostics of dementia in a large number of subjects. The project will use data from publically accessible databases such as ADNI-1/2/GO and AIBL as well as data which include different types of dementia that are available both at Imperial College and KCL. The total size of the dataset available is more than 1500 patients and controls. More...

  • Isabel Ramos
  • Sam Ellis

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

    Sam Ellis - 2014 entry

    This novel project aims to tackle a hitherto unexplored possibility for image reconstruction: direct use of two or more raw PET datasets, along with simultaneous MR data, to more optimally estimate parameters of clinical and research interest. Specifically this will involve direct estimation of voxel-level averages of kinetic and/or functional parameters and their differences between two or more scans of the same subject (for longitudinal studies). Also application may be found for direct construction of PET/MR anatomical and functional atlases from multi-subject data, ideally using diffeomorphic transformations. By dealing with the raw data directly, these tasks are expected to be performed with lower statistical noise than conventional post-processing approaches. More...

  • Camila Munoz

    Multi-parametric PET-MR imaging

    Camila Munoz - 2014 entry

    The aim of this project is to develop a multi-parametric MR acquisition by varying acquisition parameters during the MR scan and combining image reconstruction with a signal model based on these parameter changes to ensure T1 and T2 weighted MR information is obtained in a highly efficient way. This technique will then be extended with advanced regularisation approaches for a combined multi-parametric PET-MR reconstruction to optimise the diagnostic information available with simultaneous PET-MR. More...

  • Esther Puyol

    Multimodal analysis of cardiac motion and deformation

    Esther Puyol - 2014 entry

    The main aim of this project is to develop a statistical atlas of normal heart shape and function from imaging and non-imaging data (e.g. patient data from the clinical record). The atlas will be based on freely available data as well as retrospective datasets held by KCL (consisting of cine/tagged MR and 2-D/3-D ultrasound). It will be used to develop novel pattern analysis tools that extract indicators able to characterize and predict pathologies such as myocardial infarction, valve diseases, hypertrophy, and hypertension. The intended workflow of the developed system would be to make use of prior knowledge from the atlas to enable robust extraction of indicators from 2D and 3D ultrasound images, enabling early screening and characterization of pathologies. The atlas would be built from data acquired from healthy subjects, and pathological cases will be learned using tailored dissimilarity metrics with respect to the atlas. More...

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