Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques.
Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques.
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DOI：
10.1109/tmrb.2019.2949870
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发表时间：
2019-11
期刊：
影响因子：
--
通讯作者：
Krieger A
中科院分区：
文献类型：
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作者：
Saeidi H;Ge J;Kam M;Opfermann JD;Leonard S;Joshi AS;Krieger A
自主机器人手术系统旨在通过利用自动化的可重复性和一致性以及减少人为错误来改善患者的治疗效果。然而，由于这种组织缺乏结构和高度可变形性，术中自主软组织跟踪和机器人控制仍然是一个挑战。在本文中，我们利用生物相容性近红外（NIR）标记方法，为我们的智能组织自主机器人（STAR）开发了一种有监督的自主3D路径规划，过滤和控制策略，以实现复杂3D软组织的精确和一致的切口。在猪舌尸体样本上的实验结果表明，与达芬奇远程手术策略相比，该策略可将表面切口误差和深度切口误差分别降低40.03%和51.5%。此外，与基于近红外标记之间线性插值的自主路径规划方法相比，该策略利用三维组织表面信息，将切口深度误差降低了48.58%。
Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.