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基于高速图形处理器的全三维扩散光学层析成像系统。

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System.

作者信息

Saikia Manob Jyoti, Kanhirodan Rajan, Mohan Vasu Ram

机构信息

Department of Physics, Indian Institute of Science, Bangalore 560012, India.

Department of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore 560012, India.

出版信息

Int J Biomed Imaging. 2014;2014:376456. doi: 10.1155/2014/376456. Epub 2014 Apr 10.

DOI:10.1155/2014/376456
PMID:24891848
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4003791/
Abstract

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.

摘要

我们开发了一种基于图形处理器单元(GPU)的用于扩散光学断层扫描(DOT)的高速全3D系统。对于严重不适定问题的3D DOT算法,通过使用以下方法实现了执行时间的减少:(1)一种算法改进,即使用布罗伊登方法更新雅可比矩阵,从而更新参数矩阵;(2)多节点多线程GPU和CUDA(计算统一设备架构)软件架构。本研究开发了两种不同的DOT程序的GPU实现方式:(1)通过GPU CUDA和CULA例程增强的传统C语言程序(C GPU);(2)由用于GPU的MATLAB并行计算工具包支持的MATLAB程序(MATLAB GPU)。给出了C和Matlab实现方式下算法在主机CPU和GPU系统上的计算时间。正向计算使用有限元方法(FEM),问题域被离散为14610、30823和66514个四面体单元。对于基于C的GPU程序进行双平面测量时,14610个单元的DOT重建一次迭代所实现的重建时间为0.52秒。相应的基于MATLAB的GPU程序耗时为秒。如此实现的最大重建帧数为每秒2帧。 0.86

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/4c35ab6d6583/IJBI2014-376456.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/746028ef653a/IJBI2014-376456.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/30cb9a33f79f/IJBI2014-376456.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/4742d7105187/IJBI2014-376456.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/0c2972eab721/IJBI2014-376456.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/160abc2a07e5/IJBI2014-376456.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/e8531a03ab8b/IJBI2014-376456.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/8cef5f74a698/IJBI2014-376456.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/296144595575/IJBI2014-376456.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/252f96e61fa3/IJBI2014-376456.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/4c35ab6d6583/IJBI2014-376456.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/746028ef653a/IJBI2014-376456.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/30cb9a33f79f/IJBI2014-376456.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/4742d7105187/IJBI2014-376456.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/0c2972eab721/IJBI2014-376456.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/160abc2a07e5/IJBI2014-376456.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/e8531a03ab8b/IJBI2014-376456.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/8cef5f74a698/IJBI2014-376456.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/296144595575/IJBI2014-376456.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/252f96e61fa3/IJBI2014-376456.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d24/4003791/4c35ab6d6583/IJBI2014-376456.010.jpg

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本文引用的文献

1
Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography.用于漫射光学层析成像的实用全三维重建算法。
J Opt Soc Am A Opt Image Sci Vis. 2012 Jun 1;29(6):1017-26. doi: 10.1364/JOSAA.29.001017.
2
High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware.基于台式计算机和图形硬件的荧光断层成像中的高性能图像重建
Biomed Opt Express. 2011 Nov 1;2(11):3207-22. doi: 10.1364/BOE.2.003207. Epub 2011 Oct 28.
3
GPU-Accelerated Finite Element Method for Modelling Light Transport in Diffuse Optical Tomography.
用于漫射光学层析成像中光传输建模的GPU加速有限元方法
Int J Biomed Imaging. 2011;2011:403892. doi: 10.1155/2011/403892. Epub 2011 Oct 16.
4
Accelerated gradient based diffuse optical tomographic image reconstruction.基于梯度加速的扩散光学层析成像图像重建。
Med Phys. 2011 Jan;38(1):539-47. doi: 10.1118/1.3531572.
5
Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units.利用图形处理单元加速频域漫射光学断层成像图像重建。
J Biomed Opt. 2010 Nov-Dec;15(6):066009. doi: 10.1117/1.3506216.
6
Photon-measurement density functions. Part I: Analytical forms.光子测量密度函数。第一部分:解析形式。
Appl Opt. 1995 Nov 1;34(31):7395-409. doi: 10.1364/AO.34.007395.
7
Fast Monte Carlo simulations of ultrasound-modulated light using a graphics processing unit.利用图形处理单元实现超声调制光的快速蒙特卡罗模拟。
J Biomed Opt. 2010 Sep-Oct;15(5):055007. doi: 10.1117/1.3495729.
8
Quantitative evaluation of high-density diffuse optical tomography: in vivo resolution and mapping performance.高密度扩散光学断层成像的定量评估:体内分辨率和映射性能。
J Biomed Opt. 2010 Mar-Apr;15(2):026006. doi: 10.1117/1.3368999.
9
Phase-encoded retinotopy as an evaluation of diffuse optical neuroimaging.相位编码视网膜地形图作为扩散光学神经影像学的评估方法。
Neuroimage. 2010 Jan 1;49(1):568-77. doi: 10.1016/j.neuroimage.2009.07.023. Epub 2009 Jul 23.
10
Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head.用于光子在包括成人头部在内的复杂非均匀介质中迁移的三维蒙特卡罗代码。
Opt Express. 2002 Feb 11;10(3):159-70. doi: 10.1364/oe.10.000159.