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Accelerating separable footprint (SF) forward and back projection on GPU
Author(s): Xiaobin Xie; Madison G. McGaffin; Yong Long; Jeffrey A. Fessler; Minhua Wen; James Lin
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Paper Abstract

Statistical image reconstruction (SIR) methods for X-ray CT can improve image quality and reduce radiation dosages over conventional reconstruction methods, such as filtered back projection (FBP). However, SIR methods require much longer computation time. The separable footprint (SF) forward and back projection technique simplifies the calculation of intersecting volumes of image voxels and finite-size beams in a way that is both accurate and efficient for parallel implementation. We propose a new method to accelerate the SF forward and back projection on GPU with NVIDIA’s CUDA environment. For the forward projection, we parallelize over all detector cells. For the back projection, we parallelize over all 3D image voxels. The simulation results show that the proposed method is faster than the acceleration method of the SF projectors proposed by Wu and Fessler.13 We further accelerate the proposed method using multiple GPUs. The results show that the computation time is reduced approximately proportional to the number of GPUs.

Paper Details

Date Published: 9 March 2017
PDF: 8 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101322S (9 March 2017); doi: 10.1117/12.2252010
Show Author Affiliations
Xiaobin Xie, Shanghai Jiao Tong Univ. (China)
Madison G. McGaffin, Univ. of Michigan (United States)
Yong Long, Univ. of Michigan-Shanghai Jiao Tong Univ. Joint Institute (China)
Jeffrey A. Fessler, Univ. of Michigan (United States)
Minhua Wen, Shanghai Jiao Tong Univ. (China)
James Lin, Shanghai Jiao Tong Univ. (China)


Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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