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使用 dVRK 进行自主拣货和放置。

Autonomous pick-and-place using the dVRK.

机构信息

Department of Computer Science, Wellcome/EPSRC Centre for International and Surgical Sciences (WEISS), University College London, London, W1W 7EJ, UK.

Division of Surgery and Interventional Science, Department of Nanotechnology, University College London, Royal Free Hospital, London, NW3 2QG, UK.

出版信息

Int J Comput Assist Radiol Surg. 2021 Jul;16(7):1141-1149. doi: 10.1007/s11548-021-02397-y. Epub 2021 May 15.

Abstract

PURPOSE

Robotic-assisted partial nephrectomy (RAPN) is a tissue-preserving approach to treating renal cancer, where ultrasound (US) imaging is used for intra-operative identification of tumour margins and localisation of blood vessels. With the da Vinci Surgical System (Sunnyvale, CA), the US probe is inserted through an auxiliary access port, grasped by the robotic tool and moved over the surface of the kidney. Images from US probe are displayed separately to the surgical site video within the surgical console leaving the surgeon to interpret and co-registers information which is challenging and complicates the procedural workflow.

METHODS

We introduce a novel software architecture to support a hardware soft robotic rail designed to automate intra-operative US acquisition. As a preliminary step towards complete task automation, we automatically grasp the rail and position it on the tissue surface so that the surgeon is then able to manipulate manually the US probe along it.

RESULTS

A preliminary clinical study, involving five surgeons, was carried out to evaluate the potential performance of the system. Results indicate that the proposed semi-autonomous approach reduced the time needed to complete a US scan compared to manual tele-operation.

CONCLUSION

Procedural automation can be an important workflow enhancement functionality in future robotic surgery systems. We have shown a preliminary study on semi-autonomous US imaging, and this could support more efficient data acquisition.

摘要

目的

机器人辅助部分肾切除术(RAPN)是一种保留组织的治疗肾癌的方法,术中使用超声(US)成像来识别肿瘤边缘和定位血管。在达芬奇手术系统(加利福尼亚州森尼韦尔)中,US 探头通过辅助接入端口插入,由机器人工具抓住,并在肾脏表面移动。US 探头的图像与手术控制台内的手术部位视频分开显示,这使得外科医生需要解释和整合信息,这是具有挑战性的,并且使手术流程复杂化。

方法

我们引入了一种新的软件架构,以支持旨在实现术中 US 采集自动化的硬件软体机器人轨道。作为实现完全任务自动化的初步步骤,我们自动抓取轨道并将其定位在组织表面上,以便外科医生能够手动沿其操纵 US 探头。

结果

进行了一项涉及五名外科医生的初步临床研究,以评估该系统的潜在性能。结果表明,与手动遥操作相比,所提出的半自动方法减少了完成 US 扫描所需的时间。

结论

在未来的机器人手术系统中,自动化手术流程可能是增强工作流程的重要功能。我们已经展示了半自动 US 成像的初步研究,这可以支持更有效的数据采集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c43/8260407/edad74fe9e08/11548_2021_2397_Fig1_HTML.jpg

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