28 February 2013 A method for quickly and exactly extracting hepatic vein
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Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 867029 (2013) https://doi.org/10.1117/12.2006515
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qing Xiong, Qing Xiong, Rong Yuan, Rong Yuan, Luyao Wang, Luyao Wang, Yanchun Wang, Yanchun Wang, Zhen Li, Zhen Li, Daoyu Hu, Daoyu Hu, Qingguo Xie, Qingguo Xie, } "A method for quickly and exactly extracting hepatic vein", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 867029 (28 February 2013); doi: 10.1117/12.2006515; https://doi.org/10.1117/12.2006515
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