Xu Jijie, Duindam Vincent, Alterovitz Ron, Pouliot Jean, Cunha J Adam M, Hsu I-Chow, Goldberg Ken
B. Thomas Golisano College of Computing and Information Science, Rochester Institute of Technology, USA. (
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA.
Rep U S. 2009;2009:4517-4522. doi: 10.1109/iros.2009.5354787.
Accurate insertion of needles to targets in 3D anatomy is required for numerous medical procedures. To reduce patient trauma, a "fireworks" needle insertion approach can be used in which multiple needles are inserted from a single small region on the patient's skin to multiple targets in the tissue. In this paper, we explore motion planning for "fireworks" needle insertion in 3D environments by developing an algorithm based on Rapidly-exploring Random Trees (RRTs). Given a set of targets, we propose an algorithm to quickly explore the configuration space by building a forest of RRTs and to find feasible plans for multiple steerable needles from a single entry region. We present two path selection algorithms with different optimality considerations to optimize the final plan among all feasible outputs. Finally, we demonstrate the performance of the proposed algorithm with a simulation based on a prostate cancer treatment environment.
在众多医疗手术中，需要将针准确插入三维解剖结构中的目标位置。为减少患者创伤，可采用“烟花式”针插入方法，即从患者皮肤上的单个小区域向组织中的多个目标插入多根针。在本文中，我们通过开发一种基于快速扩展随机树（RRTs）的算法，探索三维环境中“烟花式”针插入的运动规划。给定一组目标，我们提出一种算法，通过构建RRTs森林快速探索配置空间，并从单个进入区域找到多根可控针的可行方案。我们提出两种具有不同最优性考虑的路径选择算法，以在所有可行输出中优化最终方案。最后，我们基于前列腺癌治疗环境进行模拟，展示了所提算法的性能。
