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High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach f...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003791/ https://www.ncbi.nlm.nih.gov/pubmed/24891848 http://dx.doi.org/10.1155/2014/376456 |
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author | Saikia, Manob Jyoti Kanhirodan, Rajan Mohan Vasu, Ram |
author_facet | Saikia, Manob Jyoti Kanhirodan, Rajan Mohan Vasu, Ram |
author_sort | Saikia, Manob Jyoti |
collection | PubMed |
description | We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second. |
format | Online Article Text |
id | pubmed-4003791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40037912014-06-02 High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System Saikia, Manob Jyoti Kanhirodan, Rajan Mohan Vasu, Ram Int J Biomed Imaging Research Article We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second. Hindawi Publishing Corporation 2014 2014-04-10 /pmc/articles/PMC4003791/ /pubmed/24891848 http://dx.doi.org/10.1155/2014/376456 Text en Copyright © 2014 Manob Jyoti Saikia 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 Saikia, Manob Jyoti Kanhirodan, Rajan Mohan Vasu, Ram High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title_full | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title_fullStr | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title_full_unstemmed | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title_short | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
title_sort | high-speed gpu-based fully three-dimensional diffuse optical tomographic system |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003791/ https://www.ncbi.nlm.nih.gov/pubmed/24891848 http://dx.doi.org/10.1155/2014/376456 |
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