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Efficient Liver Surgery Planning in 3D based on Functional Segment Classification and Volumetric Information

机译:基于功能段分类和体积信息的3D高效肝脏手术规划

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Anatomic hepatectomies are resections in which compromised segments or sectors of the liver are extracted according to the topological structure of its vascular elements. Such structure varies considerably among patients, which makes the current anatomy-based planning methods often inaccurate. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D. The method is based on standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.
机译:解剖学肝切除术是切除的切除,其中根据其血管元素的拓扑结构提取损伤的段或肝脏扇区。这种结构在患者中变化很大,这使得目前的基于解剖学的规划方法通常不准确。在这项工作中,我们提出了一种策略,以有效地和半自动细分,并在3D中分类患者特定的肝脏模型。该方法基于标准CT数据集,并允许精确估计功能剩余肝脏体积。提出了显示该方法的有效性的实验,并讨论了定量和定性结果。

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