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28 February 2007 Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?
Klaus Mueller, Fang Xu, Neophytos Neophytou
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Proceedings Volume 6498, Computational Imaging V; 64980N (2007) https://doi.org/10.1117/12.716797
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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Klaus Mueller, Fang Xu, and Neophytos Neophytou "Why do commodity graphics hardware boards (GPUs) work so well for acceleration of computed tomography?", Proc. SPIE 6498, Computational Imaging V, 64980N (28 February 2007); https://doi.org/10.1117/12.716797
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KEYWORDS
Visualization
Sensors
Field programmable gate arrays
Reconstruction algorithms
CT reconstruction
Data modeling
Computed tomography
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