Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut

The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an...

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Detalles Bibliográficos
Autores principales: Grosgeorge, Damien, Petitjean, Caroline, Dubray, Bernard, Ruan, Su
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3773378/
https://www.ncbi.nlm.nih.gov/pubmed/24069065
http://dx.doi.org/10.1155/2013/547897
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author Grosgeorge, Damien
Petitjean, Caroline
Dubray, Bernard
Ruan, Su
author_facet Grosgeorge, Damien
Petitjean, Caroline
Dubray, Bernard
Ruan, Su
author_sort Grosgeorge, Damien
collection PubMed
description The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an original method to segment in thoracic CT scans the 3D esophagus using a skeleton-shape model to guide the segmentation. Our method is composed of two steps: a 3D segmentation by graph cut with skeleton prior, followed by a 2D propagation. Our method yields encouraging results over 6 patients.
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spelling pubmed-37733782013-09-25 Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut Grosgeorge, Damien Petitjean, Caroline Dubray, Bernard Ruan, Su Comput Math Methods Med Research Article The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an original method to segment in thoracic CT scans the 3D esophagus using a skeleton-shape model to guide the segmentation. Our method is composed of two steps: a 3D segmentation by graph cut with skeleton prior, followed by a 2D propagation. Our method yields encouraging results over 6 patients. Hindawi Publishing Corporation 2013 2013-08-29 /pmc/articles/PMC3773378/ /pubmed/24069065 http://dx.doi.org/10.1155/2013/547897 Text en Copyright © 2013 Damien Grosgeorge 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 Research Article
Grosgeorge, Damien
Petitjean, Caroline
Dubray, Bernard
Ruan, Su
Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title_full Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title_fullStr Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title_full_unstemmed Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title_short Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut
title_sort esophagus segmentation from 3d ct data using skeleton prior-based graph cut
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3773378/
https://www.ncbi.nlm.nih.gov/pubmed/24069065
http://dx.doi.org/10.1155/2013/547897
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AT dubraybernard esophagussegmentationfrom3dctdatausingskeletonpriorbasedgraphcut
AT ruansu esophagussegmentationfrom3dctdatausingskeletonpriorbasedgraphcut

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