4.5 Article Proceedings Paper

Accelerating advanced MRI reconstructions on GPUs

Journal

JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
Volume 68, Issue 10, Pages 1307-1318

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jpdc.2008.05.013

Keywords

GPU computing; MRI; Reconstruction; CUDA

Funding

  1. NCI NIH HHS [R01 CA098717] Funding Source: Medline
  2. NCRR NIH HHS [P41 RR003631-15] Funding Source: Medline

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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.

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