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Proceedings Paper

GPU implementation of prior image constrained compressed sensing (PICCS)
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Paper Abstract

The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.

Paper Details

Date Published: 22 March 2010
PDF: 10 pages
Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 762239 (22 March 2010); doi: 10.1117/12.844578
Show Author Affiliations
Brian E. Nett, Univ. of Wisconsin-Madison (United States)
Jie Tang, Univ. of Wisconsin-Madison (United States)
Guang-Hong Chen, Univ. of Wisconsin-Madison (United States)


Published in SPIE Proceedings Vol. 7622:
Medical Imaging 2010: Physics of Medical Imaging
Ehsan Samei; Norbert J. Pelc, Editor(s)

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