Meet the team
Dr Matt Guy, lead for imaging physics
Dr Guy leads our imaging physics team. He has extensive experience across both diagnostic and therapeutic applications of nuclear medicine, including PET and CT scans. He has also been involved in the development of dual-energy CT imaging techniques. He's the Trust’s medical physics expert (MPE) for nuclear medicine.Read full profile
Dr James Leighs
Dr Leighs has experience in a variety of fields involving the application of computer science to physics and biology. Within the NHS, he has worked on and led projects with scientific computing, nuclear medicine, radiation protection, MRI physics, radiotherapy physics, pathology and molecular genetics. James has assisted with the supervision of STP trainees, MSc projects and post-doctoral researchers, in fields such as machine learning, medical imaging physics (MRI and nuclear medicine) and bioinformatics. James also regularly leads outreach projects for secondary school students in the fields of physics, medical physics and bioinformatics.
Despite having only worked in the healthcare sector for a relatively brief period of time, James has presented work from several projects at a number of local, national and international conferences; these include European Society for Medical Imaging Informatics (Valencia, 2016), Big Data in Medicine: Tools, Transformation and Translation (Cambridge, 2017), SPIE Medical Imaging (Houston, 2018) and Medical Imaging Understanding and Analysis (Southampton, 2018). A number of these have been funded through the successful attainment of conference scholarships.
James is interested in research projects involving the application of data science techniques to healthcare. Currently his active research interests include the search for predictive biomarkers for non-alcoholic fatty liver disease (NAFLD) in MRI, identifying chronic obstructive pulmonary disease from CT imaging and the development of automated image-processing pipelines for clinical image processing. James’s other research activities have included the development of automated imaging-dose monitoring systems, looking for patterns in HMPAO imaging data for pathological identification and predicting the results of histopathology tests from single-slice breast cancer screening images.