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Details of Grant 

EPSRC Reference: GR/N14248/01
Title: FROM MEDICAL IMAGES AND SIGNALS TO CLINICAL INFORMATION
Principal Investigator: Brady, Professor Sir JM
Other Investigators:
Todd-Pokropek, Professor A Hill, Dr D Hawkes, Professor D
Marsden, Professor P Taylor, Professor CJ Taylor, Professor C
Arridge, Professor SR Noble, Professor A Simmons, Dr A
Astley, Dr SM Thacker, Dr NA Cootes, Professor TF
Hill, Professor DL Beatty, Dr PC Buckland-Wright, Professor J
Graham, Dr J Linney, Professor A Jackson, Professor A
Tarassenko, Professor L Smith, Professor SM Delpy, Professor DT
Researcher Co-Investigators:
Project Partners:
Oxford Instruments Ltd Oxford University Innovation Ltd
Department: Engineering Science
Organisation: University of Oxford
Scheme: Standard Research (Pre-FEC)
Starts: 02 January 2001 Ends: 01 October 2007 Value (£): 8,241,936
EPSRC Research Topic Classifications:
Image & Vision Computing Instrumentation Eng. & Dev.
Intelligent & Expert Systems
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:  
Summary on Grant Application Form
Images and signals can now be obtained cost-effectively over a range of spatial and temporal scales. These offer the potential for more timely and accurate diagnosis; but the flood of data creates as many problems as opportunities. Clinicians need information not data, where information comprises data plus interpretation (clinical relevance). Transforming an unmanageable flood of data into a manageable stream of clinically relevant information presents a major challenge for IT research. The proposed IRC will provide a focus for world-class research aimed at overcoming the key scientific and technological barriers to the development of clinically effective informatics systems. To achieve a balance between scientific push and application pull, the programme will be organised around four generic themes and six scientific clinical exemplars. The themes are information fusion, robust information extraction, intelligent information acquisition, and modelling, which underpins the first three themes by providing methods for explaining observed data in terms of underlying structure and function. The six clinical exemplars are: bones and joints; stroke and brain injury; from high dependency care to home monitoring; cardiovascular disease; oncology; and minimally-invasive therapy. The aim of the IC is to develop world-class IT that addresses some of the most pressing clinical problems confronting society.
Key Findings
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Potential use in non-academic contexts
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Summary
Date Materialised
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Project URL: http://www.robots.ox.ac.uk/~irc/
Further Information:  
Organisation Website: http://www.ox.ac.uk