Author:
Driban Matthew,Yan Audrey,Selvam Amrish,Ong Joshua,Vupparaboina Kiran Kumar,Chhablani Jay
Abstract
Abstract
Background
Applications for artificial intelligence (AI) in ophthalmology are continually evolving. Fundoscopy is one of the oldest ocular imaging techniques but remains a mainstay in posterior segment imaging due to its prevalence, ease of use, and ongoing technological advancement. AI has been leveraged for fundoscopy to accomplish core tasks including segmentation, classification, and prediction.
Main body
In this article we provide a review of AI in fundoscopy applied to representative chorioretinal pathologies, including diabetic retinopathy and age-related macular degeneration, among others. We conclude with a discussion of future directions and current limitations.
Short conclusion
As AI evolves, it will become increasingly essential for the modern ophthalmologist to understand its applications and limitations to improve patient outcomes and continue to innovate.
Publisher
Springer Science and Business Media LLC
Reference119 articles.
1. Abràmoff MD, Garvin MK, Sonka M. Retinal imaging and image analysis. IEEE Rev Biomed Eng. 2010;3:169–208.
2. Panwar N, Huang P, Lee J, Keane PA, Chuan TS, Richhariya A, et al. Fundus Photography in the 21st Century–A review of recent Technological advances and their implications for Worldwide Healthcare. Telemed J E Health. 2016;22(3):198–208.
3. The Philadelphia photographer [Internet]. Philadelphia: Benerman & Wilson; 1864 [cited 2024 Mar 24]. 794 p. http://archive.org/details/philadelphiaphot18861phil.
4. Retinal Atlas. The - ClinicalKey [Internet]. [cited 2024 Mar 24]. https://www-clinicalkey-com.my.wvsom.edu:2443/#!/browse/book/3-s2.0-C20120022399.
5. Yannuzzi LA, Ober MD, Slakter JS, Spaide RF, Fisher YL, Flower RW, et al. Ophthalmic fundus imaging: today and beyond. Am J Ophthalmol. 2004;137(3):511–24.
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