Journal
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
Volume 68, Issue 10, Pages 1307-1318Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jpdc.2008.05.013
Keywords
GPU computing; MRI; Reconstruction; CUDA
Categories
Funding
- NCI NIH HHS [R01 CA098717] Funding Source: Medline
- NCRR NIH HHS [P41 RR003631-15] Funding Source: Medline
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available