深度学习在微创手术视频分析中的应用研究综述

doi:10.3969/j.issn.0258-8021.2020.04.011

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Abstract Deep learning theory has been widely used in the video analysis of minimally invasive surgery,and has made remarkable achievements in the surgical tool detection and tracking,surgical tool presence detection and workflow recognition of minimally invasive surgery. In the long run,the detailed analysis of the video content of minimally invasive surgery can not only automatically identify the ongoing surgical tasks,but also be used to remind clinicians of possible complications. In recent years,with the continuous development of technology,the application of deep learning in the video analysis of minimally invasive surgery has made great progress. This paper firstly expounded the significance,difficulties and the relevant technical content of video analysis of minimally invasive surgery,mainly introducing the advantages based on deep learning algorithm. This paper also summarized the research achievements of deep learning in the field of surgical tool detection and tracking,surgical tool presence detection and workflow recognition of minimally invasive surgery,classified and concluded algorithms based on their features in different fields of minimally invasive surgery video analysis,and evaluated their results. In the end,this paper summarized and looked forward to the future development of minimally invasive surgery video analysis.

Key words： deep learning video analysis of minimally invasive surgery fully supervision weak supervision self-supervision

Received: 13 January 2020

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R318

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	Shi Pan
	Zhao Zijian

Cite this article:

Shi Pan,Zhao Zijian. Review on the Application of Deep Learningin Video Analysis of Minimally Invasive Surgery[J]. Chinese Journal of Biomedical Engineering, 2020, 39(4): 473-484.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2020.04.011 OR http://cjbme.csbme.org/EN/Y2020/V39/I4/473

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