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  Computer-assisted analysis of arterial narrowing in whole-body MRI


   School of Computing

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Prof E Trucco  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

This project is one of six, four-year PhD Studentships funded by Medical Research Scotland (http://www.medicalresearchscotland.org.uk) to be delivered jointly by the named University and Company. The Studentships will provide the first-class academic and commercial training needed to equip the successful student for a science career in an increasingly competitive market.

Whole-body MRI clinical atheroma analysis – delivered by the University of Dundee and Toshiba Medical Visualization Systems Europe ltd (http://www.tmvse.com)

Academic Supervisors: Professor Emanuele Trucco & Professor Graeme Houston; Industrial Supervisor: Dr Robert Davey

We seek committed, capable and enthusiastic candidates for an exciting PhD project aimed to develop robust image-processing tools to detect and grade arterial narrowing (atheroma) in whole-body MRI exams.
Cardiovascular disease (CVD) is the leading cause of mortality in the UK, and was responsible for over 50,000 premature deaths in 2008. The overall annual cost in the UK is £30bn. The burden of cardiovascular disease is predicted to increase with increasing obesity, high blood pressure, type 2 diabetes and old age. While about a half (48%) of deaths are from coronary disease (CHD) ,and quarter (28%) from stroke , the burden of CVD is spread across the different vascular territories within an individual. Early identification of the severity and the distribution of CVD over the vasculature in individuals with cardiovascular syptoms would be expected to alter patient management and lead to improved patient outcomes. This staging of cardiovascular disease is analogous to the staging of the disease we undertake in cancer.
Whole body cardiovascular MRI (WBCVMR) offers a new, non-invasive, single point, comprehensive cardiovascular disease imaging assessment, which, when combined with a new quantitative analysis technique could provide the necessary assessment of CVD distribution, severity and risk of early mortality due to CVD. The key research challenge is to develop a robust image processing analytical tool that can quantify disease from the MBCVMR examination.
The project builds on the experience of two research groups at the University of Dundee: the VAMPIRE/computer vision and image processing group, led by Professor E Trucco, and the clinical radiology and cardiovascular unit, led by Professor G Houston. The team has an established track record in the key areas involved: design, implementation and validation of medical image anlysis algorithms (Trucco), imaging trials, assessing the additional value of new imaging techniques (Houston).
The project is delivered collaboratively with Toshiba Medical Visualization Systems Europe Ltd, Edinburgh, who will provide research input and with whom the student will have regular exposure. Toshiba Medical Visualization Systems Europe Ltd, Edinburgh, is a major R&D centre for Toshiba's global medical imaging business. Working in close collaboration with an industrial partner will offer a valuable opportunity to learn about the design and delivery of commercial systems. During placements at the company, the student will be part of an established research group with a track record of successful Doctoral studentships.

Funding Notes

The PhD Studentship provides: an annual tax-free stipend of £16,000, increasing to £16,500 over the four years; tuition fees at UK/EU rates only; and consumables. NB: international fees are not covered.

Applicants should have:
excellent programming skills(Windows and/or UNIX/Linux);
Masters-level degree in a numerate discipline (engineering, physics, mathematics, computer science);
basic knowledge of image processing;
commitment to learn and work as part of an interdisciplinary team in a collegiate, sharing environment.
The following will be considered an advantage:
- sound experience of MATLAB programming
- experience of medical image analysis programming
- participation in projects on biomedical image analysis