CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking

Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking...

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Main Authors: Evert van Aart, Neda Sepasian, Andrei Jalba, Anna Vilanova
Format: Article
Language:English
Published: Wiley 2011-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/2011/698908
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author Evert van Aart
Neda Sepasian
Andrei Jalba
Anna Vilanova
author_facet Evert van Aart
Neda Sepasian
Andrei Jalba
Anna Vilanova
author_sort Evert van Aart
collection DOAJ
description Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a Graphics Processing Unit (GPU). This algorithm, which is based on the calculation of geodesics, has shown promising results for both synthetic and real data, but is limited in its applicability by its high computational requirements. We present a solution which uses the parallelism offered by modern GPUs, in combination with the CUDA platform by NVIDIA, to significantly reduce the execution time of the fiber-tracking algorithm. Compared to a multithreaded CPU implementation of the same algorithm, our GPU mapping achieves a speedup factor of up to 40 times.
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institution Kabale University
issn 1687-4188
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language English
publishDate 2011-01-01
publisher Wiley
record_format Article
series International Journal of Biomedical Imaging
spelling doaj-art-7e71dbe9a89c409b982601f96263a4982025-08-20T03:35:34ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962011-01-01201110.1155/2011/698908698908CUDA-Accelerated Geodesic Ray-Tracing for Fiber TrackingEvert van Aart0Neda Sepasian1Andrei Jalba2Anna Vilanova3Department of Mathematics and Computer Science, Eindhoven University of Technology, 5600 MB Eindhove, The NetherlandsDepartment of Mathematics and Computer Science, Eindhoven University of Technology, 5600 MB Eindhove, The NetherlandsDepartment of Mathematics and Computer Science, Eindhoven University of Technology, 5600 MB Eindhove, The NetherlandsDepartment of Biomedical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The NetherlandsDiffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a Graphics Processing Unit (GPU). This algorithm, which is based on the calculation of geodesics, has shown promising results for both synthetic and real data, but is limited in its applicability by its high computational requirements. We present a solution which uses the parallelism offered by modern GPUs, in combination with the CUDA platform by NVIDIA, to significantly reduce the execution time of the fiber-tracking algorithm. Compared to a multithreaded CPU implementation of the same algorithm, our GPU mapping achieves a speedup factor of up to 40 times.http://dx.doi.org/10.1155/2011/698908
spellingShingle Evert van Aart
Neda Sepasian
Andrei Jalba
Anna Vilanova
CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
International Journal of Biomedical Imaging
title CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
title_full CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
title_fullStr CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
title_full_unstemmed CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
title_short CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
title_sort cuda accelerated geodesic ray tracing for fiber tracking
url http://dx.doi.org/10.1155/2011/698908
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AT nedasepasian cudaacceleratedgeodesicraytracingforfibertracking
AT andreijalba cudaacceleratedgeodesicraytracingforfibertracking
AT annavilanova cudaacceleratedgeodesicraytracingforfibertracking