Applications of deep learning for detecting ophthalmic diseases with ultrawide-field fundus  

作　　者：Qing-Qing Tang Xiang-Gang Yang Hong-Qiu Wang Da-Wen Wu Mei-Xia Zhang 

机构地区：[1]Department of Ophthalmology and Research Laboratory of Macular Disease,West China Hospital,Sichuan University,Chengdu 610041,Sichuan Province,China [2]Hong Kong University of Science and Technology(Guangzhou),Guangzhou 511400,Guangdong Province,China

出　　处：《International Journal of Ophthalmology(English edition)》2024年第1期188-200,共13页国际眼科杂志（英文版）

基　　金：Supported by 1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(No.ZYJC21025).

摘　　要：AIM:To summarize the application of deep learning in detecting ophthalmic disease with ultrawide-field fundus images and analyze the advantages,limitations,and possible solutions common to all tasks.METHODS:We searched three academic databases,including PubMed,Web of Science,and Ovid,with the date of August 2022.We matched and screened according to the target keywords and publication year and retrieved a total of 4358 research papers according to the keywords,of which 23 studies were retrieved on applying deep learning in diagnosing ophthalmic disease with ultrawide-field images.RESULTS:Deep learning in ultrawide-field images can detect various ophthalmic diseases and achieve great performance,including diabetic retinopathy,glaucoma,age-related macular degeneration,retinal vein occlusions,retinal detachment,and other peripheral retinal diseases.Compared to fundus images,the ultrawide-field fundus scanning laser ophthalmoscopy enables the capture of the ocular fundus up to 200°in a single exposure,which can observe more areas of the retina.CONCLUSION:The combination of ultrawide-field fundus images and artificial intelligence will achieve great performance in diagnosing multiple ophthalmic diseases in the future.

关 键 词：ultrawide-field fundus images deep learning disease diagnosis ophthalmic disease 

分 类 号：R587.2[医药卫生—内分泌] R774.5[医药卫生—内科学]