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Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey
Yang, Jie1,2; Fong, Simon1,3; Wang, Han3,4,5; Hu, Quanyi1; Lin, Chen6,7; Huang, Shigao8; Shi, Jian9; Lan, Kun1; Tang, Rui10; Wu, Yaoyang1; Zhao, Qi8
Source PublicationExpert Systems with Applications
ABS Journal Level1

Fundus digital photography and optical coherence tomography (OCT) are currently the primary imaging approaches for early diagnosis and treatment of eye diseases. In recent years, the significant development in artificial intelligence (AI), particularly in machine learning (ML) and deep learning (DL) are new and vital technical-driven motivations impacting on the traditional diagnosis and treatment methods. At the same time, the ultra-wide field (UWF) imaging technology is getting widely accepted and prevalent by its obvious advantageous features of non-dilate pupils, express-track result and the vast pool of fundus viewing angles. As a result, numerous research have been done to explore AI in ultra-wide field fundus imaging ophthalmology for joint diagnosis and treatment. However, the current review of this method is still in least ink. We first outlines the application and impact of AI technology in ophthalmic diseases in the past ten years. With the following part exclusively summarizing the technical integration of ultra-wide field fundus images and AI technology in the past four years, which has brought innovations to clinical treatment methods for the diagnosis and treatment of ophthalmic diseases; finally, we analyzed the application and implementation of the novel technology as well as the potential limitations and challenges, to predict the possibility of the technology's further principles role and values in clinical ophthalmology.

KeywordDeep Learning Machine Learning Ophthalmopathy Ultra-wide Field (Uwf) Imaging
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:000694890100001
Scopus ID2-s2.0-85106963686
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorFong, Simon; Wang, Han; Tang, Rui
Affiliation1.Department of Computer and Information Science, University of Macau, China
2.Chongqing Industry &Trade Polytechnic, Chongqing, China
3.Medical Devices R&D Centre, ZIAT Chinese Academy of Sciences, Zhuhai, China
4.Faculty of Data Science, City University of Macau, China
5.Beijing Institute of Technology, Zhuhai, China
6.Department of Ophthalmology, People's Hospital of ShenZhen, Shenzhen, China, China
7.School of Optometry, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
8.Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, China
9.Wisney Medical (Shenzhen) Co. Ltd, Shenzhen, China
10.Department of Management Science and Information System, Faculty of Management and Economics, Kunming University of Science and Technology, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yang, Jie,Fong, Simon,Wang, Han,et al. Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey[J]. Expert Systems with Applications,2021,182.
APA Yang, Jie,Fong, Simon,Wang, Han,Hu, Quanyi,Lin, Chen,Huang, Shigao,Shi, Jian,Lan, Kun,Tang, Rui,Wu, Yaoyang,&Zhao, Qi.(2021).Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey.Expert Systems with Applications,182.
MLA Yang, Jie,et al."Artificial intelligence in ophthalmopathy and ultra-wide field image: A survey".Expert Systems with Applications 182(2021).
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