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Research on 3D crack segmentation of CT images of oil rock core

In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image ba...

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Detalles Bibliográficos
Autores principales: Zou, Yongning, Yao, Gongjie, Wang, Jue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516274/
https://www.ncbi.nlm.nih.gov/pubmed/34648545
http://dx.doi.org/10.1371/journal.pone.0258463
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author Zou, Yongning
Yao, Gongjie
Wang, Jue
author_facet Zou, Yongning
Yao, Gongjie
Wang, Jue
author_sort Zou, Yongning
collection PubMed
description In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results.
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spelling pubmed-85162742021-10-15 Research on 3D crack segmentation of CT images of oil rock core Zou, Yongning Yao, Gongjie Wang, Jue PLoS One Research Article In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results. Public Library of Science 2021-10-14 /pmc/articles/PMC8516274/ /pubmed/34648545 http://dx.doi.org/10.1371/journal.pone.0258463 Text en © 2021 Zou et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zou, Yongning
Yao, Gongjie
Wang, Jue
Research on 3D crack segmentation of CT images of oil rock core
title Research on 3D crack segmentation of CT images of oil rock core
title_full Research on 3D crack segmentation of CT images of oil rock core
title_fullStr Research on 3D crack segmentation of CT images of oil rock core
title_full_unstemmed Research on 3D crack segmentation of CT images of oil rock core
title_short Research on 3D crack segmentation of CT images of oil rock core
title_sort research on 3d crack segmentation of ct images of oil rock core
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516274/
https://www.ncbi.nlm.nih.gov/pubmed/34648545
http://dx.doi.org/10.1371/journal.pone.0258463
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