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Marc Modat is a Reader at King's College London, specializing in Biomedical Life Sciences. His research focuses on medical image registration, where he is the main developer of NiftyReg, an open-source software designed for efficient image registration. Over the years, Marc has developed various techniques for near real-time registration, as well as biomechanically constrained models and symmetric invertible diffeomorphisms. His work also includes application-tailored algorithms for surgical guidance in brain and musculoskeletal interventions. NiftyReg has been adopted in large-scale clinical research studies and clinical trials. His research interests delve into developing novel imaging biomarkers, particularly for monitoring elderly brain health using magnetic resonance imaging and positron emission tomography. Additionally, Marc has been involved in creating algorithmic tools for surgical planning and guidance, utilizing model-based machine learning approaches. He has contributed to the setup and deployment of data analytics platforms that ensure secure data transfer and automated processing, which are currently in use for extensive international clinical studies.
King's College London • London, GB
Focused on research and development in biomedical engineering and medical imaging.
Requirements are consistent across King's Business School and Social Science & Public Policy departments for standard Master's entries.