基于计算机视觉的干眼检测算法综述  

A Review of Dry Eye Detection Algorithms Based on Computer Vision

作　　者：刘俊[1] 张志 万光荣 林铭炜[2] LIU Jun;ZHANG Zhi;WAN Guangrong;LIN Mingwei(School of Software Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;College of Computer and Cyber Security,Fujian Normal University,Fuzhou 350117,China)

机构地区：[1]重庆邮电大学软件工程学院,重庆400065 [2]福建师范大学计算机与网络空间安全学院,福建福州350117

出　　处：《福建师范大学学报（自然科学版）》2024年第6期19-29,共11页Journal of Fujian Normal University：Natural Science Edition

基　　金：国家自然科学基金资助项目(62307008);重庆市自然科学基金资助项目(cstc2021jcyj-msxmX0530)。

摘　　要：对当前干眼检测算法的研究进展进行总结和分析。首先,介绍干眼症基本概念和识别干眼症的重要指标。其次,将现有检查方法和算法按照泪河高度检查、泪膜破裂时间测定、睑板腺功能检查进行介绍和分析。通过对不同算法的总结和分析,比较各自算法的优点并归纳缺点。最后,对待解决的相关问题进行讨论,并展望干眼检测未来发展趋势。This review aims to summarize and analyze the current research progress in dry eye detection algorithms.Firstly,the basic concepts of dry eye and the important indicators for its diagnosis are introduced.Next,existing examination methods and algorithms are presented and analyzed according to important indicators such as tear meniscus height examination,tear film break-up time determination,and meibomian gland function examination.Through the summary and analysis of different algorithms,the advantages of each algorithm are compared and the disadvantages are summarized.Finally,unresolved issues are discussed,and future trends in dry eye detection are anticipated.

关 键 词：干眼症 泪河高度 泪膜破裂时间 睑板腺 深度学习 

分 类 号：TP399[自动化与计算机技术—计算机应用技术] R77[自动化与计算机技术—计算机科学与技术]