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It is essential for physicians to obtain the accurate venous tree from abdominal CT angiography (CTA) series in order to carry out the preoperative planning and intraoperative navigation for hepatic surgery. In this process, one of the important tasks is to separate the given liver venous mask into its hepatic and portal parts. In this paper, we present a novel method for liver venous tree separation. The proposed method first concentrates on extracting potential vessel intersection points between hepatic and portal venous systems. Then, the proposed method focuses on modeling the vessel intersection neigh-borhoods with a robust twin-line random sample consensus (RANSAC) shape detector. Finally, the proposed method conducts the venous tree separation based on the results of the twin-line RANSAC as well as physical constraints posed by Murray's Law. We test our method on 22 clinical CTA series and demonstrate its effectiveness.
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Yan et al. (2017) studied this question.
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