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Proceedings Paper

Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?
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Paper Abstract

Commodity graphics hardware boards (GPUs) have achieved remarkable speedups in various sub-areas of Computed Tomography (CT). This paper takes a close look at the GPU architecture and its programming model and describes a successful acceleration of Feldkamp's cone-beam CT reconstruction algorithm. Further, we will also have a comparative look at the new emerging Cell architecture in this regard, which similar to GPUs has also seen its first deployment in gaming and entertainment. To complete the discussion on high-performance PC-based computing platforms, we will also compare GPUs with FPGA (Field Programmable Gate Array) based medical imaging solutions.

Paper Details

Date Published: 28 February 2007
PDF: 12 pages
Proc. SPIE 6498, Computational Imaging V, 64980N (28 February 2007); doi: 10.1117/12.716797
Show Author Affiliations
Klaus Mueller, Stony Brook Univ. (United States)
Fang Xu, Stony Brook Univ. (United States)
Neophytos Neophytou, Stony Brook Univ. (United States)


Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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