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F.A.U.S.T.

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Flexible Application of Uncertainty for Scanning and Tracking

"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 c... ver más

30/04/2015

IMPERIAL COLLEGE O...

231K€

Presupuesto del proyecto: 231K€

Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2015-04-30 No tenemos la información de la convocatoria

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1 Participantes

IMPERIAL COLLEGE OF SCIENCE...

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Líder del proyecto

IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND ME... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 231K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "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.."

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