基于遗传算法的认知规划在计算机辅助干预中的应用

Wan Cheng Lim, Hongliang Ren
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引用次数: 1

摘要

由于临床结果的改善,微创和计算机辅助干预和手术正被患者和临床医生广泛接受。新的模式涉及更先进的医疗器械,其中射频消融(RFA)是一种使用针状电极杀死肿瘤组织的干预手段。本文提出了一种计算优化算法来规划最佳消融递送,并有可能在手术机器人中实现认知规划。采用遗传算法来设计肿瘤消融规划系统,因为遗传算法可以考虑肿瘤消融规划系统的多目标特性。提出了一种数学协议,为算法的可行性提供了参考。通过仿真和实际数据验证了遗传算法的可行性;并发现能够为肿瘤消融规划问题生成可接受的解决方案集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive planning based on Genetic Algorithm in computer-assisted interventions
Minimally invasive and computer-assisted interventions and surgeries are getting widely accepted by patients and clinicians due to improved clinical outcomes. The new paradigm involves more advanced medical instruments, among which Radiofrequency Ablation (RFA) is one type of intervention to kill tumor tissues using a needle-like electrode. In this paper, a computational optimization algorithm to plan optimal ablation delivery is proposed, and potentially allows cognitive planning in surgical robotics. Genetic Algorithm (GA) was used as it can be designed to consider the multi-objective nature of a tumor ablation planning system. A mathematical protocol was also proposed to provide a reference for the viability of the algorithm. The feasibility of GA was tested on simulated and real data; and was found to be able to generate acceptable solution set for the tumor ablation planning problems.
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