Paper
22 March 2010 TV-regularized iterative image reconstruction on a mobile C-ARM CT
Yongsheng Pan, Ross Whitaker, Arvi Cheryauka, Dave Ferguson
Author Affiliations +
Abstract
3D computed tomography has been extensively studied and widely used in modern society. Although most manufacturers choose the filtered backprojection algorithm (FBP) for its accuracy and efficiency, iterative reconstruction methods have a significant potential to provide superior performance for incomplete, noisy projection data. However, iterative methods have a high computational cost, which hinders their practical use. Furthermore, regularization is usually required to reduce the effects of noise. In this paper, we analyze the use of the Simultaneous Algebraic Reconstruction Technique (SART) with total variation (TV) regularization. Additionally, graphics hardware is utilized to increase the speed of SART. NVIDIA's GPU and Compute Unified Device Architecture (CUDA) comprise the core of our computational platform. GPU implementation details, including ray-based forward projection and voxel-based backprojection are illustrated. Experimental results for high-resolution synthetic and real data are provided to demonstrate the accuracy and efficiency of the proposed framework.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongsheng Pan, Ross Whitaker, Arvi Cheryauka, and Dave Ferguson "TV-regularized iterative image reconstruction on a mobile C-ARM CT", Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76222L (22 March 2010); https://doi.org/10.1117/12.844398
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CITATIONS
Cited by 10 scholarly publications and 2 patents.
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KEYWORDS
Reconstruction algorithms

Computed tomography

Sensors

Fluctuations and noise

Head

Image restoration

Visualization

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