计算机视觉在麻醉学中的应用进展  

Progress on the application of computer vision in anesthesiology

作　　者：李昊鹏 王宇 姚尚龙[1] Li Haopeng;Wang Yu;Yao Shanglong(Department of Anesthesiology,Union Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430022,China)

机构地区：[1]华中科技大学同济医学院附属协和医院麻醉科,武汉430022

出　　处：《国际麻醉学与复苏杂志》2024年第3期313-316,共4页International Journal of Anesthesiology and Resuscitation

摘　　要：计算机视觉(CV)在麻醉学中的应用已日渐显现其潜力和价值,CV技术可以提高麻醉效果、降低并发症风险、优化资源分配和提高工作效率。文章回顾了CV在麻醉学中的现有应用,包括气道管理、神经阻滞和穿刺、麻醉深度(DoA)监测和围手术期相关并发症预警等;也讨论了当前应用中面临的挑战,如数据获取、模型训练、解释性、鲁棒性等;以及未来可能的发展方向,如采用混合学习、迁移学习和联邦学习等新的方法或技术。CV技术有望对麻醉学的发展产生深远影响,推动其向更高的精准医疗水平迈进。The application of computer vision(CV)in anesthesiology is gradually showing its potential and value,capable of enhancing the effectiveness of anesthesia,reducing the risk of complications,optimizing resource distribution,and improving work effi⁃ciency.This article reviews the current applications of CV in anesthesiology,including airway management,nerve blocks and punc⁃tures,monitoring the depth of anesthesia(DoA),and warning of perioperative-related complications.Meanwhile,it discusses the chal⁃lenges faced in the current application,such as data acquisition,model training,interpretability,and robustness,and potential direc⁃tions of future development,such as adopting new methods or technologies like mixed learning,transfer learning,and federated learn⁃ing.CV is expected to profoundly affect the development of anesthesiology,promoting it to a higher level of precision medical care.

关 键 词：计算机视觉 围手术期 机器学习 机械通气 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] R614[自动化与计算机技术—计算机科学与技术]