Email: alejandro.frangi@manchester.ac.uk

Research profile and key clinical specialties

Professor Frangi is the Bicentennial Turing Chair in Computational Medicine and a Royal Academy of Engineering Chair in Emerging Technologies at The University of Manchester, UK, with joint appointments at the School of Health Sciences (Division of Informatics, Imaging and Data Science) and the School of Engineering (Department of Computer Science).

He is also member of the Pankhurst Institute for Healthcare Technologies and the Institute for Artificial Intelligence and Data Science. He is a Turing Fellow at the Alan Turing Institute and directs the Centre for Computational Imaging and Modelling in Medicine (CIMIM).

Prof Frangi’s main research interests lie at the crossroads of medical image analysis and modelling, emphasising machine learning (phenomenological models) and computational physiology (mechanistic models).

He has interests in statistical methods applied to population imaging phenomics and in silico clinical trials. His highly interdisciplinary work has been translated to the areas of cardiovascular, musculoskeletal and neurosciences.

Two key publications

• Sarrami-Foroushani A, Lassila T, MacRaild M, Asquith J, Roes KCB, Byrne JV, Frangi AF. In-silico trial of intracranial flow diverters replicates and expands insights from conventional clinical trials. Nat Commun (IF: 14.92; Q1). 2021 Jun 23;12(1):3861. See https://vimeo.com/578167974.
• Xia Y, Zhang L, Ravikumar N, Attar R, Piechnik SK, Neubauer S, Petersen SE, Frangi AF. Recovering from missing data in population imaging – Cardiac MR image imputation via conditional generative adversarial nets. Med Image Anal (IF: 8.54; Q1). 2021 Jan;67:101812.

Possible PhD projects

• AI and machine learning in medical imaging interpretation. ML in imaging-genetics
• Personalised computational modelling for interventional planning and guidance
• In silico trials of cardiovascular medical devices

More information

In Manchester I direct the Centre for Computational Imaging and Modeling in Medicine. I serve on the Editorial Board of Medical Image Analysis, IEEE Trans Medical Imaging, IEE Trans Artificial Intelligence, and IEEE Trans Computational Imaging.

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Keywords: Computational Imaging, AI, Mechanistic Modelling, Cardiovascular, Musculoskeletal, Computational Phenomics, In Silico Methods

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