Wei, Wei;
Anantharanjit, Rajeevan;
Patel, Radhika Pooja;
Cordeiro, Maria Francesca;
(2023)
Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence.
Expert Review of Molecular Diagnostics
, 23
(6)
pp. 485-494.
10.1080/14737159.2023.2208751.
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Abstract
INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment worldwide. The endpoint of AMD, both in its dry or wet form, is macular atrophy (MA) which is characterized by the permanent loss of the RPE and overlying photoreceptors either in dry AMD or in wet AMD. A recognized unmet need in AMD is the early detection of MA development. AREAS COVERED: Artificial Intelligence (AI) has demonstrated great impact in detection of retinal diseases, especially with its robust ability to analyze big data afforded by ophthalmic imaging modalities, such as color fundus photography (CFP), fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). Among these, OCT has been shown to have great promise in identifying early MA using the new criteria in 2018. EXPERT OPINION: There are few studies in which AI-OCT methods have been used to identify MA; however, results are very promising when compared to other imaging modalities. In this paper, we review the development and advances of ophthalmic imaging modalities and their combination with AI technology to detect MA in AMD. In addition, we emphasize the application of AI-OCT as an objective, cost-effective tool for the early detection and monitoring of the progression of MA in AMD.
| Type: | Article |
|---|---|
| Title: | Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/14737159.2023.2208751 |
| Publisher version: | https://doi.org/10.1080/14737159.2023.2208751 |
| Language: | English |
| Additional information: | © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
| Keywords: | Age-related macular degeneration; artificial intelligence; deep learning; macular atrophy; machine learning; optical coherence tomography |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10172124 |
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