Visual detection and tracking algorithms for minimally invasive surgical instruments: A comprehensive review of the state-of-the-art

计算机科学 手术机器人 手术器械 手术计划 人工智能 机器人 机器人学 计算机视觉 跟踪(教育) 算法 医学 外科 心理学 教育学
作者
Yan Wang,Qi Sun,Zhenzhong Liu,Lin Gu
出处
期刊:Robotics and Autonomous Systems [Elsevier BV]
卷期号:149: 103945-103945 被引量:31
标识
DOI:10.1016/j.robot.2021.103945
摘要

Minimally invasive surgical instrument visual detection and tracking is one of the core algorithms of minimally invasive surgical robots. With the development of machine vision and robotics, related technologies such as virtual reality, three-dimensional reconstruction, path planning, and human–machine collaboration can be applied to surgical operations to assist clinicians or use surgical robots to complete clinical operations. The minimally invasive surgical instrument vision detection and tracking algorithm analyzes the image transmitted by the surgical robot endoscope, extracting the position of the surgical instrument tip in the image, so as to provide the surgical navigation. This technology can greatly improve the accuracy and success rate of surgical operations. The purpose of this paper is to further study the visual detection and tracking technology of minimally invasive surgical instruments, summarize the existing research results, and apply it to the surgical robot project. By reading the literature, the author summarized the theoretical basis and related algorithms of this technology in recent years. Finally, the author compares the accuracy, speed and application scenario of each algorithm, and analyzes the advantages and disadvantages of each algorithm. The papers included in the review were selected through Web of Science, Google Scholar, PubMed and CNKI searches using the keywords: “object detection”, “object tracking”, “surgical tool detection”, “surgical tool tracking”, “surgical instrument detection” and “surgical instrument tracking” limiting results to the year range 1985–2021. Our study shows that this technology will have a great development prospect in the aspects of accuracy and real-time improvement in the future.

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