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Details of Grant 

EPSRC Reference: EP/N014588/1
Title: EPSRC Centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging
Principal Investigator: Aston, Professor JAD
Other Investigators:
Gilbert, Professor FJ Bohndiek, Dr Sarah Hansen, Dr A
Burnet, Professor NG Reichelt, Dr S Fokas, Professor A
Williams, Dr GB Bullmore, Professor E Rudd, Dr J
Samworth, Professor RJ Treece, Dr GM Schönlieb, Dr C
Researcher Co-Investigators:
Project Partners:
AstraZeneca Cambridge Computed Imaging Ltd Cambridge University Hospitals Trust
Microsoft Siemens
Department: Pure Maths and Mathematical Statistics
Organisation: University of Cambridge
Scheme: Standard Research
Starts: 01 March 2016 Ends: 29 February 2020 Value (£): 1,923,014
EPSRC Research Topic Classifications:
Med.Instrument.Device& Equip. Numerical Analysis
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
09 Sep 2015 Maths in Healthcare - Interviews Announced
Summary on Grant Application Form
Applied Mathematics and Statistics are routinely seen as separate disciplines. However, many of the methodological challenges in image analysis, particularly from the types of multiscale multimodal images available from Neurological, Cardiovascular and Oncology imaging, illustrate that a combined approach, dissolving intradisciplinary mathematical boundaries, is the only possible way forward if a step-change in image analysis of combined data is to occur. This Centre will foster links between applied maths and statistics, particularly high dimensional and functional statistical analysis with applied and computational numerical analysis, through the focus on multimodal imaging data. The Centre proposes to provide a research focus on bringing state-of-the-art mathematical tools to clinical end users through collaborations both within mathematics and between mathematics and healthcare professionals, particularly those in oncology, cardiovascular medicine and neurology. This will ultimately lead to new mathematical frontiers, joining statistics and computational mathematics, as well as a move away from individual image analysis to a holistic approach to all available imaging, from the cellular to systems scale, for clinical diagnosis, prognosis and treatment planning.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Organisation Website: http://www.cam.ac.uk