Automated detection of age-related macular degeneration in color fundus photography: a systematic review

E. Pead; R. Megaw; J. Cameron; A. Fleming; B. Dhillon; E. Trucco; T. MacGillivray

doi:10.1016/j.survophthal.2019.02.003

Automated detection of age-related macular degeneration in color fundus photography: a systematic review

E. Pead, R. Megaw, J. Cameron, A. Fleming, B. Dhillon, E. Trucco, T. MacGillivray

Research output: Contribution to journal › Article › peer-review

Abstract

The rising prevalence of age-related eye diseases, particularly age-related macular degeneration, places an ever-increasing burden on health care providers. As new treatments emerge, it is necessary to develop methods for reliably assessing patients' disease status and stratifying risk of progression. The presence of drusen in the retina represents a key early feature in which size, number, and morphology are thought to correlate significantly with the risk of progression to sight-threatening age-related macular degeneration. Manual labeling of drusen on color fundus photographs by a human is labor intensive and is where automatic computerized detection would appreciably aid patient care. We review and evaluate current artificial intelligence methods and developments for the automated detection of drusen in the context of age-related macular degeneration.

Original language	English
Pages (from-to)	498-511
Number of pages	14
Journal	Survey of Ophthalmology
Volume	64
Issue number	4
Early online date	14 Feb 2019
DOIs	https://doi.org/10.1016/j.survophthal.2019.02.003 https://doi.org/10.1016/j.survophthal.2019.02.003
Publication status	Published - 18 Feb 2019

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Tom MacGillivray
- t.j.macgillivrayed.acuk
- Deanery of Clinical Sciences - Senior Research Fellow
Person: Academic: Research Active (Research Assistant)

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abstract = "The rising prevalence of age-related eye diseases, particularly age-related macular degeneration, places an ever-increasing burden on health care providers. As new treatments emerge, it is necessary to develop methods for reliably assessing patients' disease status and stratifying risk of progression. The presence of drusen in the retina represents a key early feature in which size, number, and morphology are thought to correlate significantly with the risk of progression to sight-threatening age-related macular degeneration. Manual labeling of drusen on color fundus photographs by a human is labor intensive and is where automatic computerized detection would appreciably aid patient care. We review and evaluate current artificial intelligence methods and developments for the automated detection of drusen in the context of age-related macular degeneration.",

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AU - Fleming, A.

AU - Dhillon, B.

AU - Trucco, E.

AU - MacGillivray, T.

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Automated detection of age-related macular degeneration in color fundus photography: a systematic review

Abstract

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