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Title: A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

Abstract

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization modelmore » is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.« less

Authors:
; ; ; ; ; ;  [1]
  1. National Digital Switching System Engineering and Technological Research Center, Zhengzhou, Henan 450002 (China)
Publication Date:
OSTI Identifier:
22597711
Resource Type:
Journal Article
Resource Relation:
Journal Name: Review of Scientific Instruments; Journal Volume: 87; Journal Issue: 8; Other Information: (c) 2016 Author(s); Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; ALGORITHMS; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; COMPUTERIZED TOMOGRAPHY; IMAGES; ITERATIVE METHODS; MINIMIZATION; NONDESTRUCTIVE TESTING; VARIATIONS; X RADIATION

Citation Formats

Zhang, Wenkun, Zhang, Hanming, Li, Lei, Wang, Linyuan, Cai, Ailong, Li, Zhongguo, and Yan, Bin, E-mail: ybspace@hotmail.com. A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization. United States: N. p., 2016. Web. doi:10.1063/1.4958898.
Zhang, Wenkun, Zhang, Hanming, Li, Lei, Wang, Linyuan, Cai, Ailong, Li, Zhongguo, & Yan, Bin, E-mail: ybspace@hotmail.com. A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization. United States. doi:10.1063/1.4958898.
Zhang, Wenkun, Zhang, Hanming, Li, Lei, Wang, Linyuan, Cai, Ailong, Li, Zhongguo, and Yan, Bin, E-mail: ybspace@hotmail.com. 2016. "A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization". United States. doi:10.1063/1.4958898.
@article{osti_22597711,
title = {A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization},
author = {Zhang, Wenkun and Zhang, Hanming and Li, Lei and Wang, Linyuan and Cai, Ailong and Li, Zhongguo and Yan, Bin, E-mail: ybspace@hotmail.com},
abstractNote = {X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.},
doi = {10.1063/1.4958898},
journal = {Review of Scientific Instruments},
number = 8,
volume = 87,
place = {United States},
year = 2016,
month = 8
}
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