F.A.U.S.T.
Flexible Application of Uncertainty for Scanning and Tracking
| Coordinatore | IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
Organization address
address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 231˙283 € |
| EC contributo | 231˙283 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2012-IEF |
| Funding Scheme | MC-IEF |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-05-01 - 2015-04-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
Organization address
address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD contact info |
UK (LONDON) | coordinator | 231˙283.20 |
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Obiettivo del progetto (Objective)
'F.A.U.S.T. -- 'Flexible Application of Uncertainty for Scanning and Tracking' proposes to integrate uncertainty information about medical image processing methods completely into the clinical work flow. This requires to solve computational problems that arise when different algorithms try to monopolize the available hardware. These problems becomes even more demanding for algorithms that are accelerated by Graphics Processing Units (GPUs). To overcome the current shortcomings of recent programming methods for GPUs, the fellow will use a novel GPU-accelerated framework, which he has developed during his previous career together with his colleagues form Graz University of Technology as a base. During the proposed project, the fellow will first adapt this framework to make scheduled and prioritized execution of GPU-accelerated medical segmentation and registration algorithms feasible, subsequently apply and evaluate this framework for existing algorithms and further develop a concurrent real-time visualization of uncertainties, which are currently neglected during medical standard procedures. To proof the flexibility and applicability of the proposed methods, the fellow will finally develop a novel Magnetic Resonance Imaging (MRI) scanner steering method, which is based on uncertainty information and which will allow to evaluate the organs of a moving foetus within the uterus. In contrast to Ultrasound-based imaging, the proposed new method will allow an earlier and more accurate diagnosis of malformations and foetal diseases and will enable treatments in time. Thereby, the fellow will draw on his rich experience with GPU accelerated three-dimensional and four-dimensional medical volume processing and will provide unseen interactive results in the course of F.A.U.S.T..'