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Variable Weighted Ordered Subset Image Reconstruction Algorithm

We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geomet...

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Detalles Bibliográficos
Autores principales: Pan, Jinxiao, Zhou, Tie, Han, Yan, Jiang, Ming
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2324020/
https://www.ncbi.nlm.nih.gov/pubmed/23165012
http://dx.doi.org/10.1155/IJBI/2006/10398
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author Pan, Jinxiao
Zhou, Tie
Han, Yan
Jiang, Ming
author_facet Pan, Jinxiao
Zhou, Tie
Han, Yan
Jiang, Ming
author_sort Pan, Jinxiao
collection PubMed
description We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively.
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spelling pubmed-23240202008-04-22 Variable Weighted Ordered Subset Image Reconstruction Algorithm Pan, Jinxiao Zhou, Tie Han, Yan Jiang, Ming Int J Biomed Imaging Article We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively. Hindawi Publishing Corporation 2006 2006-10-12 /pmc/articles/PMC2324020/ /pubmed/23165012 http://dx.doi.org/10.1155/IJBI/2006/10398 Text en Copyright © 2006 J. Pan et al. https://creativecommons.org/licenses/by/3.0/ 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 Article
Pan, Jinxiao
Zhou, Tie
Han, Yan
Jiang, Ming
Variable Weighted Ordered Subset Image Reconstruction Algorithm
title Variable Weighted Ordered Subset Image Reconstruction Algorithm
title_full Variable Weighted Ordered Subset Image Reconstruction Algorithm
title_fullStr Variable Weighted Ordered Subset Image Reconstruction Algorithm
title_full_unstemmed Variable Weighted Ordered Subset Image Reconstruction Algorithm
title_short Variable Weighted Ordered Subset Image Reconstruction Algorithm
title_sort variable weighted ordered subset image reconstruction algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2324020/
https://www.ncbi.nlm.nih.gov/pubmed/23165012
http://dx.doi.org/10.1155/IJBI/2006/10398
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AT zhoutie variableweightedorderedsubsetimagereconstructionalgorithm
AT hanyan variableweightedorderedsubsetimagereconstructionalgorithm
AT jiangming variableweightedorderedsubsetimagereconstructionalgorithm