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Proceedings Paper

Nonlocal means-based regularizations for statistical CT reconstruction
Author(s): Hao Zhang; Jianhua Ma; Yan Liu; Hao Han; Lihong Li; Jing Wang; Zhengrong Liang
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Paper Abstract

Statistical iterative reconstruction (SIR) methods have shown remarkable gains over the conventional filtered backprojection (FBP) method in improving image quality for low-dose computed tomography (CT). They reconstruct the CT images by maximizing/minimizing a cost function in a statistical sense, where the cost function usually consists of two terms: the data-fidelity term modeling the statistics of measured data, and the regularization term reflecting a prior information. The regularization term in SIR plays a critical role for successful image reconstruction, and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) algorithm in image processing applications, we proposed, in this work, a family of generic and edgepreserving NLM-based regularizations for SIR. We evaluated one of them where the potential function takes the quadratic-form. Experimental results with both digital and physical phantoms clearly demonstrated that SIR with the proposed regularization can achieve more significant gains than SIR with the widely-used Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation.

Paper Details

Date Published: 19 March 2014
PDF: 8 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 903337 (19 March 2014); doi: 10.1117/12.2043949
Show Author Affiliations
Hao Zhang, Stony Brook Univ. (United States)
Jianhua Ma, Stony Brook Univ. (United States)
Southern Medical Univ. (China)
Yan Liu, Stony Brook Univ. (United States)
Hao Han, Stony Brook Univ. (United States)
Lihong Li, CUNY, College of Staten Island (United States)
Jing Wang, The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)
Zhengrong Liang, Stony Brook Univ. (United States)

Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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