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Segmentation using Sparse Shape Composition and minimally supervised method in liver surgery planning system

机译:肝脏手术规划系统中使用稀疏形状组成和最小监督方法的分割

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Liver surgery planning system plays an important role in achieving the optimized surgery plan in Living Donor Liver Transplantation (LDLT). Segmentation of liver is a very challenging component in liver surgery planning systems. Patient-specific shape prior is of great significance in improving the robustness of liver segmentation. However, complex liver shape variations among different patients are difficult to model, which affects the accurate segmentation in liver surgery planning. To address this problem, we incorporated the Sparse Shape Composition (SSC) in the computer assisted liver surgery planning system. The basic modules of the system consist of: (1) Segmentation module. The Sparse Shape Composition (SSC) model is employed to get a patient-specific liver shape prior and then the shape prior is combined with a minimally supervised method to segment the liver parenchyma, hepatic vessels and tumors simultaneously. (2) Approximation of liver segments. It divides the liver into several functionally independent segments. (3) Visualization module. The result of clinical experiment shows this system has a good performance in providing accurate and robust liver surgery planning.
机译:肝脏手术规划系统在实现活体肝移植(LDLT)的优化外科计划方面发挥着重要作用。肝脏的分割是肝脏手术规划系统中具有非常具有挑战性的组分。患者特异性形状在提高肝脏分割的稳健性方面具有重要意义。然而,不同患者之间的复杂肝脏形状变异是难以模拟的,这会影响肝脏手术规划中的准确细分。为了解决这个问题,我们在计算机辅助肝脏手术计划系统中纳入了稀疏形状组成(SSC)。系统的基本模块包括:(1)分段模块。使用稀疏形状组合物(SSC)模型以获得患者特异性肝脏形状,然后将其形状与最小监督的方法组合以同时分段肝实质,肝血管和肿瘤。 (2)肝脏近似。它将肝脏分成几个功能独立的段。 (3)可视化模块。临床实验结果表明该系统具有良好的性能,提供准确和强大的肝脏手术规划。

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