Our CDT training programme has three core research themes; from the acquisition, processing and integration of imaging information that can be provided for an individual patient, all the way from cell to tissue, organ and system levels and from anatomical to molecular and cellular targets. Progress in medical imaging research is underpinned by parallel developments in a broad range of complementary disciplines. Advancing research at the intersections of these fields represents one of the most promising strategies for developing imaging technologies that will have a major clinical impact.
Students interested in applying to the CDT should consider their background and select the stream that is most suitable.
Read more about our available PhD projects and view the 'How to apply page' if you are interested in applying.
Medical imaging has become an essential tool for clinical diagnosis, treatment and monitoring, playing an important role in the improvement of public health. Nowadays a variety of imaging techniques, including x-ray, CT, ultrasound, magnetic resonance imaging (MRI), positron emission tomography (PET) and nuclear medicine, are routinely used in medical practices. However, despite significant advances during the last decades, researches aim to further improve these imaging techniques, to enhance the information and clinical value provided by the images, and to develop new imaging acquisitions including simultaneous multi modality imaging.
Medical imaging comprises two main processes: a) image acquisition and b) image reconstruction. Image acquisition refers to the collection of data required to form an image, whereas image reconstruction refers to the process of actually generating an image from the acquired data (termed as “inverse problem”). These two processes are closely related and improvements in both areas are required to enhance the information in the images and to allow faster data acquisition and reconstruction.
Our research focuses on clinically relevant problems by tackling some of the major technical challenges in the acquisition of the different image modalities. Those include achieving higher sensitivity, better resolution, improved contrast, reduced image artefacts due to physiological motion, as well as the synergistic combination of different imaging modalities (e.g. PET-MRI).
Appropriate first degrees: Physics, Electrical Engineering and Biomedical Engineering.
Our research targets clinical relevant problems by tackling some of the major technical challenges in image reconstruction of the different imaging modalities. Those include reduction of radiation dose in case of ionizing techniques, compensation of physiological motion during the acquisition, speed up of the acquisition by developing undersampled reconstruction techniques such as compressed sensing, as well as model based reconstruction methods to improve the accuracy of the images in clinically relevant anomalies. This is generally achieved trough mathematical modelling and nonlinear iterative optimization.
Appropriate first degrees: Physics, Electrical Engineering, Biomedical Engineering, Applied Mathematics, and Computer Sciences.
The chemists and biologists work together, in collaboration with many internal and external clinicians and biologists, to identify targets for molecular imaging (such as changes in metabolism, gene expression, molecular receptors, cell death, hypoxia) associated with disease and its response to treatment, and to design and develop contrast agents that can ultimately be used in patients for imaging. While the majority of molecular imaging agents use radionuclides (positron or gamma emitters) to provide the signal, some are based on paramagnetic complexes and nanoparticles (for MRI), fluorescent and luminescent or bioluminescent probes (for optical imaging) or microbubbles (for ultrasound imaging). The molecular targeting may be achieved by coupling radionuclides to biomolecules such as peptides and proteins, or built into the design of small molecules and metal complexes.
Below is a PET image of hypoxia in head and neck cancer using Cu-64-ATSM
Below is PET imaging of mouse thyroid using F-18-tetrafluoroborate
A major part of the chemistry challenge is not only to design and construct the radiopharmaceuticals but to develop highly efficient chemistry to perform the radiolabelling with the utmost speed and simplicity of manipulation, to avoid radiation dose to the operator and decay of the radionuclide and minimise opportunities for microbial contamination. The biological behaviour of the new probes is evaluated in tissue culture and small animal imaging to optimise design and identify opportunities for translation to the clinic, and molecular biology is used to design and produce new protein based probes. The range of chemistry is very broad, encompassing organic small molecules, metal complexes, proteins, peptides and nanoparticles. Many radionuclides, spanning the whole periodic table, are in regular use in the Centre: 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 and immunological areas. MR spectroscopy with P-31 and hyperpolarised C-13 is use to investigate metabolism in tissues. A major focus is development of methodology for tracking the migration, survival and differentiation of cells within the body.
Appropriate first degrees: Chemistry, Biology, Biochemistry, Pharmacy
This stream aims to develop novel, computational techniques for biophysical modelling and biomedical image computing. Research in this stream ranges from methodology driven research that focuses on blue-sky research in image computing and computation modelling, to research that focuses on the translation of advanced computing and modelling technology into clinical practice addressing real-world problems in healthcare. The research in these topics is underpinned by mathematical modeling, numerical methods software engineering, and high performance computing.
Possible PhD topics include:
Appropriate first degree: Computer Science, Mathematics, Physics, Biomedical Engineering or another engineering-related discipline.