工作区
计算机科学
成像体模
机器人
可视化
计算机视觉
工作流程
基准标记
渲染(计算机图形)
立体定向
人工智能
手术计划
医学物理学
体绘制
放射科
医学
触觉技术
数据库
作者
Farid Tavakkolmoghaddam,Dhruv Kool Rajamani,Benjamin Szewczyk,Zhanyue Zhao,Katie Gandomi,Shreyas Chandra Sekhar,Julie G. Pilitsis,Christopher J. Nycz,Gregory S. Fischer
标识
DOI:10.1109/ismr48346.2021.9661581
摘要
The adoption of robotic image-guided surgeries has enabled physicians to perform therapeutic and diagnostic procedures with less invasiveness and higher accuracy. One example is the MRI-guided stereotactic robotic-assisted surgery for conformal brain tumor ablation, where the robot is used to position and orient a thin probe to target a desired region within the brain. Requirements such as the remote center of motion and precise manipulation, impose the use of complex kinematic structures, which result in non-trivial workspaces in these robots. The lack of workspace visualization poses a challenge in selecting valid entry and target points during the surgical planning and navigation stage. In this paper, we present a surgical planning toolkit called the "NeuroPlan" for our MRI-compatible stereotactic neurosurgery robot developed as a module for 3D Slicer software. This toolkit streamlines the current surgical workflow by rendering and overlaying the robot's reachable workspace on the MRI image. It also assists with identifying the optimal entry point by segmenting the cranial burr hole volume and locating its center. We demonstrate the accuracy of the workspace rendering and burr hole parameter detection through both phantom and MR-images acquired from previously conducted animal studies.
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