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This project will involve developing new ways of data mining dynamic MRI datasets with the goal of helping clinicians to better understand the workings of the human digestive system. This goal offers the potential for developing non invasive diagnostic tools, or biomarkers that would make a real difference to the speed and accuracy of clinical decisions. To briefly summarise, we will develop measures that characterise how MR images change over time, then look for ways to relate these time series summaries to known clinical conditions. There will be some image processing but the major research focus of the project will be in data mining, with a particular emphasis on time series data mining. Some background in data mining and/or image processing is desirable but not essential. The successful candidate will have excellent programming and analytical skills and a good degree in computer science.
Funding Notes:
Funding may be available for UK/EU students. If funding is awarded for this project it will cover tuition fees and stipend for UK students. EU students may be eligible for full funding, or tuition fees only, depending on the funding source. International students will not be eligible for this funding however they are still welcome to apply for this project but would have to find alternative funding. Self funded students are also welcome to apply.
References:
A. P. Toms, A. Farghal, B. Kasmai, A. Bagnall and P. N. Malcolm, Physiology of the small bowel: a new approach using MRI and proposal for a new metric of function. Medical Hypotheses. 76(6):834-9, 2011