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Biography
Michael is Professor of Biomedical Imaging and Deputy Head of School in the School of Medicine, he is a member of the Sir Peter Mansfield Imaging Centre and the Beacon of Excellence in Precision Imaging. He is also a Visiting Professor at Trinity College Dublin, an honorary Senior Fellow in the Wellcome Centre for Integrative Neuroimaging in Oxford and a Junior Fellow of the International Society for Magnetic Resonance in Medicine.
Michael is a series editor of the Oxford Neuroimaging Primers (www.neuroimagingprimers.org), author of The Principles of Medical Imaging for Engineers, and co-author of Physiology for Engineers (www.physiologyforengineers.org). He is also a member of the Editorial Board of the journal Neuroimage.
Michael was previously an Associate Professor of Engineering Science at the Institute of Biomedical Engineering, University of Oxford, and Director of Training for the EPSRC-MRC Centre for Doctoral Training in Biomedical Imaging. In Oxford, Michael's Quantitative Biomedical Inference (QUBIc) group developed probabilistic analysis methods for physiological imaging, allowing imaging devices to be used to make spatially resolved measurements of physiological processes such as perfusion.
Prior to working in medical image analysis, Michael did his doctorate in SCUBA diving and developed machine learning methods for the detection of landmines in his masters project. His undergraduate degree was in Engineering Science at Oxford.
Expertise Summary
Michael has a background in the mathematical modelling of physiology, Bayesian inference method, machine learning techniques, and the development of image analysis algorithms. Much of his recent research has focused on the quantitative spatial mapping of physiological quantities, such as perfusion, from medical imaging devices for use in clinical research and practice.
Michael is concerned not only with developing new methods for the analysis of data, but their wider use in the research community and beyond. To this end his group develops software and associated documentation and training from their novel research. This includes a GUI-based package for the analysis of a range of physiological imaging data (www.quantiphyse.org) and a number of tools within the FMRIB Software Library (www.fmrib.ox.ac.uk/fsl) used in the Neuroimaging community, particularly BASIL (asl-docs.readthedocs.io) for quantifying cerebral perfusion.
Teaching Summary
Michael is a Senior Fellow of the Higher Education Academy recognising his teaching contributions for postgraduate researchers through a number of Centres for Doctoral training (Healthcare… read more
Research Summary
Michael leads the PhysImAls (www.physiamls.org), whose research focuses on the development of novel analysis methods that enable medical imaging to be used to make spatially resolved measurements of… read more
Michael is a Senior Fellow of the Higher Education Academy recognising his teaching contributions for postgraduate researchers through a number of Centres for Doctoral training (Healthcare Innovation, Biomedical Imaging), for the imaging research community through education courses and textbooks, and the training of future biomedical engineers through textbooks and course development.
Michael is a series editor and author on the Oxford Neuroimaging Primer series (www.neuroimagingprimers.org). This series of books, online exercises and appendices, provides a practical and hands-on guide to the world of analysis neuroimaging data. Michael has particular expertise in perfusion imaging analysis and is a regular contributor to the FSL course and ISMRM Educational Programme.
Michael was previously Director of Training for the EPSRC-MRC Centre for Doctoral Training in Biomedical Imaging (a joint initiative between the Universities of Oxford and Nottingham) and also served as an Associate Director for the EPSRC Centre for Doctoral Training in Healthcare Innovation in Oxford.
Michael is the co-author of Physiology for Engineers and author of the Principles of Medical of Medical Imaging for Engineers (www.physiologyforengineers.org), both of which are aimed at aspiring biomedical engineers and other physical scientist who want an introduction to the world of physiology and medical imaging. Michael previously taught on the undergraduate Engineering Science degree at the University of Oxford.
Current Research
Michael leads the PhysImAls (www.physiamls.org), whose research focuses on the development of novel analysis methods that enable medical imaging to be used to make spatially resolved measurements of physiological processes in living organisms, most notably in the study of diseases in patients.
The PhysImAl group develops software tools to enable wider dissemination of their methods and the greater adoption of physiological imaging methods in basic and clinical science studies. Their main software outputs are:
- Quantiphyse - a GUI-based software product for physiological image analysis, including tools for quantification of physiology from a wide range of different data.
- BASIL - a toolbox for perfusion quantification in the brain using Arterial Spin Labelling MRI, distributed as part of the FMRIB Software Library.
Much of Michael's research has been in brain imaging, including developing methods for the quantification of perfusion and other haemodynamics using MRI methods such as Arterial Spin Labelling, as well as techniques for extracting information on the cellular environment (such as pH) using Chemical Exchange Saturation Transfer MRI. Through a range of collaborations Michael contributes to research projects in acute stroke, brain tumours and dementia.
Past Research
Before joining the Sir Peter Mansfield Centre in Nottingham, Michael led the Quantitative Biomedical Inference (QUBIc) group, based at the Institute of Biomedical Engineering in Oxford. This group developed probabilistic analysis methods for physiological imaging. Michael was previously Image Analysis Theme lead for the CRUK Oxford Centre for Cancer Imaging and the Image Analysis Workgroup leader for the COST Action on Arterial Spin Labelling in Dementia.