NDLI: Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

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Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Content Provider	Scilit
Author	Zhang, Han-Ming Wang, Lin-Yuan Yan, Bin Lin-Yuan, Wang Xi, Xiao-Qi Lu, Li-Zhong
Copyright Year	2013
Description	Journal: Chinese Physics B Linear scan computed tomography (LCT) is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation (TV) minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method (ADM) to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.
Related Links	http://iopscience.iop.org/article/10.1088/1674-1056/22/7/078701/pdf
ISSN	16741056
e-ISSN	20583834
DOI	10.1088/1674-1056/22/7/078701
Journal	Chinese Physics B
Issue Number	7
Volume Number	22
Language	English
Publisher	IOP Publishing
Publisher Date	2013-07-01
Access Restriction	Open
Subject Keyword	Journal: Chinese Physics B Applied Mathematics Interdisciplinary Mathematics Alternating Direction Method Total Variation Linear Scan Ct Image Reconstruction
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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