|Affiliation||University of Manchester|
|Research area code||(B0) Broadly-based programmes within subjects allied to medicine|
|Fellowship Inauguration Year||2021|
Developing software to support high quality research in the field of medical image analysis, with a particular focus on translating new methods from computer vision, machine learning and statistical modelling into clinically useful applications.
I am a research associate at the University of Manchester, currently working in the Quantitative Biomedical Imaging (QBI, http://qbi-lab.org/) Laboratory, a small research team that specialises in providing analysis of medical images for clinical and research trials.
I studied computer science as an undergraduate, and have subsequently worked in the field of medical image analysis, completing a PhD in 2010 at the University of Manchester, where I have remained ever since.
During my career have developed a passion for producing software to support imaging research, both for my own work, and writing and deploying applications directly used by clinicians and technicians in research trials. These applications have supported a wide array of research projects, generating results for many high-profile publications, and producing data used in several on-going projects.
I currently manage the codebase for the QBI lab, and in particular Madym (https://gitlab.com/manchester_qbi/manchester_qbi_public/madym_cxx) - an open source library for analysing DCE-MRI data, written in C++ with wrappers available for Matlab and Python. I am also working on OSIPI (https://www.osipi.org/ - the open source initiative for perfusion imaging), an international collaboration of researchers working to promote the sharing of perfusion imaging software.
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