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Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image
Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction per...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4808793/ https://www.ncbi.nlm.nih.gov/pubmed/27066107 http://dx.doi.org/10.1155/2016/5836410 |
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author | Guo, Jingyu Qi, Hongliang Xu, Yuan Chen, Zijia Li, Shulong Zhou, Linghong |
author_facet | Guo, Jingyu Qi, Hongliang Xu, Yuan Chen, Zijia Li, Shulong Zhou, Linghong |
author_sort | Guo, Jingyu |
collection | PubMed |
description | Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges. |
format | Online Article Text |
id | pubmed-4808793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-48087932016-04-10 Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image Guo, Jingyu Qi, Hongliang Xu, Yuan Chen, Zijia Li, Shulong Zhou, Linghong Comput Math Methods Med Research Article Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges. Hindawi Publishing Corporation 2016 2016-01-26 /pmc/articles/PMC4808793/ /pubmed/27066107 http://dx.doi.org/10.1155/2016/5836410 Text en Copyright © 2016 Jingyu Guo et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Guo, Jingyu Qi, Hongliang Xu, Yuan Chen, Zijia Li, Shulong Zhou, Linghong Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title | Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title_full | Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title_fullStr | Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title_full_unstemmed | Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title_short | Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image |
title_sort | iterative image reconstruction for limited-angle ct using optimized initial image |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4808793/ https://www.ncbi.nlm.nih.gov/pubmed/27066107 http://dx.doi.org/10.1155/2016/5836410 |
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