title: Functional Region Annotation of Liver CT Image Based on Vascular Tree.
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.
authors.affiliation: Research Center of CAD, Tongji University, Shanghai 200092, China.
authors.forename: Yufei
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Research Center of CAD, Tongji University, Shanghai 200092, China; School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
authors.forename: Xiaodong
authors.identifier: 0000-0002-0536-1345
authors.initials: X
authors.lastname: Yue
authors.affiliation: College of Science and Technology, Ningbo University, Ningbo 315211, China.
authors.forename: Caiming
authors.identifier: 0000-0001-5126-8849
authors.initials: C
authors.lastname: Zhong
authors.affiliation: Research Center of CAD, Tongji University, Shanghai 200092, China; School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China.
authors.forename: Gang
authors.initials: G
authors.lastname: Wang
mesh_terms: D006801:Humans; D008099:Liver / Q000098:blood supply* / Q000000981:diagnostic imaging*; D008955:Models, Cardiovascular; D014057:Tomography, X-Ray Computed