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Fly Algorithm in PET Reconstruction for Radiotherapy Treatment Planning


This project is focused on developing new software technologies for lung cancer treatment and it is based on accurate physical models implemented using high performance computing. Four research themes have been identified: i) improvement of our original reconstruction algorithm for Positron Emission Tomography (PET) imaging, ii) fast respiration simulation, iii) tumour segmentation and extraction, and iv) interactive multi-modal visualisation. The clinical outputs that are expected are as follows: i) improvement of quantitative results in PET, ii) assisted elaboration of treatment plans using both anatomical (CT) and “biological” (PET) information, iii) assisted therapeutic monitoring to assess the response of tumours to the treatment, and iv) improvement of the validation of treatment plans by radiation oncologists.

This multi-disciplinary project -- at the interface between medical physics, computer science, and medicine -- will require for its success an alliance with external partners in computer science (INRIA Saclay, France; Lorraine University, France; and Ghent University Belgium), medicine (University of Paris 13 / Hôpital Avicenne, France; and Wales Research and Diagnostic Positron Emission Tomography Imaging Centre (PETIC), United Kingdom), and medical physics (Léon Bérard cancer treatment and research center, Lyon, France; and Department of Radiation Oncology at University of California San Diego).

The PI is a new lecturer who brings a broad experience of research in computer science and medical physics. If successful, it will be his first grant award and will enable him to establish a novel research area at Bangor University. It will result in a collaboration with international partners that will grow in future.

Call for proposal

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College road
LL57 2DG Bangor
United Kingdom

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Wales West Wales and The Valleys Gwynedd
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Christine Davey (Mrs.)
EU contribution
€ 100 000,00