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Accelerating advanced MRI reconstructions on GPUs

delete2008-10-01
delete199
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OA
AI
S
Sam S. Stone *
J
Justin P. Haldar
S
Stephanie C. Tsao
W
Wen mei Hwu
B
Bradley P. Sutton
Z
Zhi‐Pei Liang
DOI:10.1016/j.jpdc.2008.05.013delete
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摘要

摘要

En 中文
Computational acceleration on graphics processing units (GPUs) can make advanced magnetic resonance imaging (MRI) reconstruction algorithms attractive in clinical settings, thereby improving the quality of MR images across a broad spectrum of applications. This paper describes the acceleration of such an algorithm on NVIDIA's Quadro FX 5600. The reconstruction of a 3D image with 128(3) voxels achieves up to 180 GFLOPS and requires just over one minute on the Quadro, while reconstruction on a quad-core CPU is twenty-one times slower. Furthermore, for the data set studied in this article. the percent error exhibited by the advanced reconstruction is roughly three times lower than the percent error incurred by conventional reconstruction techniques. (c) 2008 Elsevier Inc. All rights reserved.
Keyword:
GPU computing
MRI
Reconstruction
CUDA
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期刊

Journal of Parallel and Distributed Computing 封面图
Journal of Parallel and Distributed Computing
IF:
4
论文数:
3.8K
被引数:
4.8K

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U
University of Illinois Urbana-Champaign
学者数:
2.4W
论文数: 2.0W
被引数: 35
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University of Illinois System
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6.9W
论文数: 6.2W
被引数: 644
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