Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Glaucoma management in the era of artificial intelligence

Devalla, Sripad Krishna, Liang, Zhang, Pham, Tan Hung, Boote, Craig ORCID: https://orcid.org/0000-0003-0348-6547, Strouthidis, Nicholas G, Thiery, Alexandre H and Girard, Michael J A 2020. Glaucoma management in the era of artificial intelligence. British Journal of Ophthalmology 104 (3) , pp. 301-311. 10.1136/bjophthalmol-2019-315016

Full text not available from this repository.

Abstract

Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature makes it difficult to diagnose until a late stage. The diagnosis of glaucoma is a complicated and expensive effort that is heavily dependent on the experience and expertise of a clinician. The application of artificial intelligence (AI) algorithms in ophthalmology has improved our understanding of many retinal, macular, choroidal and corneal pathologies. With the advent of deep learning, a number of tools for the classification, segmentation and enhancement of ocular images have been developed. Over the years, several AI techniques have been proposed to help detect glaucoma by analysis of functional and/or structural evaluations of the eye. Moreover, the use of AI has also been explored to improve the reliability of ascribing disease prognosis. This review summarises the role of AI in the diagnosis and prognosis of glaucoma, discusses the advantages and challenges of using AI systems in clinics and predicts likely areas of future progress.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Optometry and Vision Sciences
Publisher: BMJ Publishing Group
ISSN: 0007-1161
Date of Acceptance: 5 October 2019
Last Modified: 26 Oct 2022 07:58
URI: https://orca.cardiff.ac.uk/id/eprint/126295

Citation Data

Cited 41 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item