Current applications of artificial intelligence-based computer vision in laparoscopic surgery

Recent advances in artificial intelligence (AI) have sparked a surge in the application of computer vision (CV) in surgical video analysis. Laparoscopic surgery produces a large number of surgical videos, which provides a new opportunity for improving of CV technology in laparoscopic surgery. AI-bas...

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Bibliographic Details
Published inLaparoscopic, endoscopic, and robotic surgery Vol. 6; no. 3; pp. 91 - 96
Main Authors Guo, Kangwei, Tao, Haisu, Zhu, Yilin, Li, Baihong, Fang, Chihua, Qian, Yinling, Yang, Jian
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.09.2023
KeAi Communications Co., Ltd
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Summary:Recent advances in artificial intelligence (AI) have sparked a surge in the application of computer vision (CV) in surgical video analysis. Laparoscopic surgery produces a large number of surgical videos, which provides a new opportunity for improving of CV technology in laparoscopic surgery. AI-based CV techniques may leverage these surgical video data to develop real-time automated decision support tools and surgeon training systems, which shows a new direction in dealing with the shortcomings of laparoscopic surgery. The effectiveness of CV applications in surgical procedures is still under early evaluation, so it is necessary to discuss challenges and obstacles. The review introduced the commonly used deep learning algorithms in CV and described their usage in detail in four application scenes, including phase recognition, anatomy detection, instrument detection and action recognition in laparoscopic surgery. The currently described applications of CV in laparoscopic surgery are limited. Most of the current research focuses on the identification of workflow and anatomical structure, while the identification of instruments and surgical actions is still awaiting further breakthroughs. Future research on the use of CV in laparoscopic surgery should focus on applications in more scenarios, such as surgeon skill assessment and the development of more efficient models.
ISSN:2468-9009
2468-9009
DOI:10.1016/j.lers.2023.07.001