Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yufei, Yue, Xiaodong, Zhong, Caiming, Wang, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
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
_version_ 1782468680137834496
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
work_keys_str_mv AT chenyufei functionalregionannotationofliverctimagebasedonvasculartree
AT yuexiaodong functionalregionannotationofliverctimagebasedonvasculartree
AT zhongcaiming functionalregionannotationofliverctimagebasedonvasculartree
AT wanggang functionalregionannotationofliverctimagebasedonvasculartree