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Functional Region Annotation of Liver CT Image Based on Vascular Tree.
Chen, Yufei; Yue, Xiaodong; Zhong, Caiming; Wang, Gang.
Affiliation
  • Chen Y; Research Center of CAD, Tongji University, Shanghai 200092, China.
  • Yue X; Research Center of CAD, Tongji University, Shanghai 200092, China; School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
  • Zhong C; College of Science and Technology, Ningbo University, Ningbo 315211, China.
  • Wang G; Research Center of CAD, Tongji University, Shanghai 200092, China; School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China.
Biomed Res Int ; 2016: 5428737, 2016.
Article in En | MEDLINE | ID: mdl-27891516
ABSTRACT
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, X-Ray Computed / Liver / Models, Cardiovascular Limits: Humans Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, X-Ray Computed / Liver / Models, Cardiovascular Limits: Humans Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country: