Autonomous Robot-Assisted Video Capture in Open Cardiac Surgery: Surgical Field Detection and Obstacle-Aware Viewpoint Planning via CHELS

IF 2.4 3区医学 Q2 SURGERY

International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2026-03-04 DOI:10.1002/rcs.70149

Juntao Gao, Yueri Cai, Hongjia Zhang, Ming Gong

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引用次数: 0

Abstract

Background

Traditional surgical video recording requires professional personnel to manually adjust the camera capturing position, which leads to low recording efficiency and interference with the surgical process.

Method

To address these issues, this study proposes an automatic surgical video capture scheme based on an intelligent surgical video capture robot system. The method utilises the YOLO v5 algorithm and a 3D camera to identify and localise the surgical field area. Additionally, Convex Hull Edge Line Search (CHELS) algorithm is constructed to rapidly solve the optimal capturing position while avoiding obstacles. Finally, Position-Based Visual Servoing (PBVS) is applied to control the camera for precise capture of the surgical field.

Result

The detection model for the surgical field achieved an [email protected] of 0.962, and the average solution time of the CHELS is 0.1469s.

Conclusion

Automatic surgical video capture schemes can efficiently enable the intelligent and automatic recording of surgical videos.

查看原文本刊更多论文

自主机器人辅助视频采集在心脏直视手术中的应用：通过CHELS进行手术视野检测和障碍物感知视点规划。

背景：传统的手术视频录制需要专业人员手动调整摄像机拍摄位置，导致录制效率低，干扰手术过程。方法：针对这些问题，本研究提出了一种基于智能手术视频采集机器人系统的手术视频自动采集方案。该方法利用YOLO v5算法和3D相机来识别和定位手术野区域。此外，构造了凸壳边缘线搜索（CHELS）算法，在避开障碍物的同时快速求解最优捕获位置。最后，采用基于位置的视觉伺服（PBVS）控制摄像机，实现手术视野的精确捕获。结果：手术野检测模型的准确率mAP@0.5为0.962，CHELS平均溶液时间为0.1469s。结论：手术视频自动采集方案能有效实现手术视频的智能化、自动化记录。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.