Comparison of Optimization Algorithms for a Tubular Aspiration Robot for Maximum Coverage in Intracerebral Hemorrhage Evacuation

J. Granna, Yi Guo, K. Weaver, J. Burgner-Kahrs
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引用次数: 9

Abstract

Intracerebral hemorrhage evacuation (ICH) using a tubular aspiration robot promises benefits over conventional approaches to release the pressure of an hemorrhage within the brain. The blood of the hemorrhage is evacuated through preplanned, coordinated motion of a flexible, curved, concentric tube that aspirates from within the hemorrhage. To achieve maximum decompression, the curvature of the inner aspirator tube has to be selected such that its workspace covers the hemorrhage. As the use of multiple aspiration tubes sequentially is advisable, one can perform an exhaustive search over all possible aspiration tube shapes as has been previously proposed in the literature. In this paper, we introduce a new optimization algorithm which is computationally more efficient and thus allows for quick optimization during surgery. To demonstrate its performance and compare it to the previously proposed exhaustive search algorithm, we present experimental evaluation results on 175 simulated patient trials.
最大覆盖脑出血引流管式机器人优化算法比较
使用管状抽吸机器人的脑出血清除(ICH)有望比传统方法更有效地释放颅内出血的压力。出血的血液通过一个灵活的、弯曲的同心管的预先计划的、协调的运动从出血中抽吸出来。为了达到最大程度的减压,必须选择内吸引管的曲率,使其工作空间覆盖出血。由于顺序使用多个抽吸管是可取的,因此可以像以前在文献中提出的那样,对所有可能的抽吸管形状进行详尽的搜索。在本文中,我们介绍了一种新的优化算法,该算法计算效率更高,从而允许在手术过程中快速优化。为了证明其性能并将其与先前提出的穷举搜索算法进行比较,我们给出了175个模拟患者试验的实验评估结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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