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Proceedings Paper

A method for quickly and exactly extracting hepatic vein
Author(s): Qing Xiong; Rong Yuan; Luyao Wang; Yanchun Wang; Zhen Li; Daoyu Hu; Qingguo Xie
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Paper Abstract

It is of vital importance that providing detailed and accurate information about hepatic vein (HV) for liver surgery planning, such as pre-operative planning of living donor liver transplantation (LDLT). Due to the different blood flow rate of intra-hepatic vascular systems and the restrictions of CT scan, it is common that HV and hepatic portal vein (HPV) are both filled with contrast medium during the scan and in high intensity in the hepatic venous phase images. As a result, the HV segmentation result obtained from the hepatic venous phase images is always contaminated by HPV which makes accurate HV modeling difficult. In this paper, we proposed a method for quick and accurate HV extraction. Based on the topological structure of intra-hepatic vessels, we analyzed the anatomical features of HV and HPV. According to the analysis, three conditions were presented to identify the nodes that connect HV with HPV in the topological structure, and thus to distinguish HV from HPV. The method costs less than one minute to extract HV and provides a correct and detailed HV model even with variations in vessels. Evaluated by two experienced radiologists, the accuracy of the HV model obtained from our method is over 97%. In the following work, we will extend our work to a comprehensive clinical evaluation and apply this method to actual LDLT surgical planning.

Paper Details

Date Published: 28 February 2013
PDF: 6 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 867029 (28 February 2013); doi: 10.1117/12.2006515
Show Author Affiliations
Qing Xiong, Huazhong Univ. of Science and Technology (China)
Wuhan National Lab. for Optoelectronics (China)
Rong Yuan, Huazhong Univ. of Science and Technology (China)
Wuhan National Lab. for Optoelectronics (China)
Luyao Wang, Huazhong Univ. of Science and Technology (China)
Wuhan National Lab. for Optoelectronics (China)
Yanchun Wang, Tongji Medical College, Huazhong Univ. of Science and Technology (China)
Zhen Li, Tongji Medical College, Huazhong Univ. of Science and Technology (China)
Daoyu Hu, Tongji Medical College, Huazhong Univ. of Science and Technology (China)
Qingguo Xie, Huazhong Univ. of Science and Technology (China)
Wuhan National Lab. for Optoelectronics (China)


Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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