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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...

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Detalles Bibliográficos
Autores principales: Saikia, Manob Jyoti, Kanhirodan, Rajan, Mohan Vasu, Ram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
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.
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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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