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Functional Region Annotation of Liver CT Image Based on Vascular Tree
Anatomical analysis of liver region is critical in diagnosis and treatment of liver diseases. The reports of liver region annotation are helpful for doctors to precisely evaluate liver system. One of the challenging issues is to annotate the functional regions of liver through analyzing Computed Tom...
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/PMC5116550/ https://www.ncbi.nlm.nih.gov/pubmed/27891516 http://dx.doi.org/10.1155/2016/5428737 |
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author | Chen, Yufei Yue, Xiaodong Zhong, Caiming Wang, Gang |
author_facet | Chen, Yufei Yue, Xiaodong Zhong, Caiming Wang, Gang |
author_sort | Chen, Yufei |
collection | PubMed |
description | Anatomical analysis of liver region is critical in diagnosis and treatment of liver diseases. The reports of liver region annotation are helpful for doctors to precisely evaluate liver system. One of the challenging issues is to annotate the functional regions of liver through analyzing Computed Tomography (CT) images. In this paper, we propose a vessel-tree-based liver annotation method for CT images. The first step of the proposed annotation method is to extract the liver region including vessels and tumors from the CT scans. And then a 3-dimensional thinning algorithm is applied to obtain the spatial skeleton and geometric structure of liver vessels. With the vessel skeleton, the topology of portal veins is further formulated by a directed acyclic graph with geometrical attributes. Finally, based on the topological graph, a hierarchical vascular tree is constructed to divide the liver into eight segments according to Couinaud classification theory and thereby annotate the functional regions. Abundant experimental results demonstrate that the proposed method is effective for precise liver annotation and helpful to support liver disease diagnosis. |
format | Online Article Text |
id | pubmed-5116550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-51165502016-11-27 Functional Region Annotation of Liver CT Image Based on Vascular Tree Chen, Yufei Yue, Xiaodong Zhong, Caiming Wang, Gang Biomed Res Int Research Article Anatomical analysis of liver region is critical in diagnosis and treatment of liver diseases. The reports of liver region annotation are helpful for doctors to precisely evaluate liver system. One of the challenging issues is to annotate the functional regions of liver through analyzing Computed Tomography (CT) images. In this paper, we propose a vessel-tree-based liver annotation method for CT images. The first step of the proposed annotation method is to extract the liver region including vessels and tumors from the CT scans. And then a 3-dimensional thinning algorithm is applied to obtain the spatial skeleton and geometric structure of liver vessels. With the vessel skeleton, the topology of portal veins is further formulated by a directed acyclic graph with geometrical attributes. Finally, based on the topological graph, a hierarchical vascular tree is constructed to divide the liver into eight segments according to Couinaud classification theory and thereby annotate the functional regions. Abundant experimental results demonstrate that the proposed method is effective for precise liver annotation and helpful to support liver disease diagnosis. Hindawi Publishing Corporation 2016 2016-11-07 /pmc/articles/PMC5116550/ /pubmed/27891516 http://dx.doi.org/10.1155/2016/5428737 Text en Copyright © 2016 Yufei Chen 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 Chen, Yufei Yue, Xiaodong Zhong, Caiming Wang, Gang Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title | Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title_full | Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title_fullStr | Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title_full_unstemmed | Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title_short | Functional Region Annotation of Liver CT Image Based on Vascular Tree |
title_sort | functional region annotation of liver ct image based on vascular tree |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116550/ https://www.ncbi.nlm.nih.gov/pubmed/27891516 http://dx.doi.org/10.1155/2016/5428737 |
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