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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176496/ https://www.ncbi.nlm.nih.gov/pubmed/21941525 http://dx.doi.org/10.1155/2011/698908 |
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author | van Aart, Evert Sepasian, Neda Jalba, Andrei Vilanova, Anna |
author_facet | van Aart, Evert Sepasian, Neda Jalba, Andrei Vilanova, Anna |
author_sort | van Aart, Evert |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-3176496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-31764962011-09-22 CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking van Aart, Evert Sepasian, Neda Jalba, Andrei Vilanova, Anna Int J Biomed Imaging Research Article 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. Hindawi Publishing Corporation 2011 2011-09-20 /pmc/articles/PMC3176496/ /pubmed/21941525 http://dx.doi.org/10.1155/2011/698908 Text en Copyright © 2011 Evert van Aart et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article van Aart, Evert Sepasian, Neda Jalba, Andrei Vilanova, Anna CUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking |
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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3176496/ https://www.ncbi.nlm.nih.gov/pubmed/21941525 http://dx.doi.org/10.1155/2011/698908 |
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