Journal article
Progress on retinal image analysis for age related macular degeneration
Progress in Retinal and Eye Research, Vol.38, pp.20-42
01/2014
DOI: 10.1016/j.preteyeres.2013.10.002
PMID: 24211245
Abstract
Age-related macular degeneration (AMD) is the leading cause of vision loss in those over the age of 50 years in the developed countries. The number is expected to increase by ∼1.5 fold over the next ten years due to an increase in aging population. One of the main measures of AMD severity is the analysis of drusen, pigmentary abnormalities, geographic atrophy (GA) and choroidal neovascularization (CNV) from imaging based on color fundus photograph, optical coherence tomography (OCT) and other imaging modalities. Each of these imaging modalities has strengths and weaknesses for extracting individual AMD pathology and different imaging techniques are used in combination for capturing and/or quantification of different pathologies. Current dry AMD treatments cannot cure or reverse vision loss. However, the Age-Related Eye Disease Study (AREDS) showed that specific anti-oxidant vitamin supplementation reduces the risk of progression from intermediate stages (defined as the presence of either many medium-sized drusen or one or more large drusen) to late AMD which allows for preventative strategies in properly identified patients. Thus identification of people with early stage AMD is important to design and implement preventative strategies for late AMD, and determine their cost-effectiveness. A mass screening facility with teleophthalmology or telemedicine in combination with computer-aided analysis for large rural-based communities may identify more individuals suitable for early stage AMD prevention. In this review, we discuss different imaging modalities that are currently being considered or used for screening AMD. In addition, we look into various automated and semi-automated computer-aided grading systems and related retinal image analysis techniques for drusen, geographic atrophy and choroidal neovascularization detection and/or quantification for measurement of AMD severity using these imaging modalities. We also review the existing telemedicine studies which include diagnosis and management of AMD, and how automated disease grading could benefit telemedicine. As there is no treatment for dry AMD and only early intervention can prevent the late AMD, we emphasize mass screening through a telemedicine platform to enable early detection of AMD. We also provide a comparative study between the imaging modalities and identify potential study areas for further improvement and future research direction in automated AMD grading and screening.
Details
- Title: Subtitle
- Progress on retinal image analysis for age related macular degeneration
- Creators
- Yogesan Kanagasingam - Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization (CSIRO), 65 Brockway Road, Floreat, Underwood Avenue, WA 6014, AustraliaAlauddin Bhuiyan - Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organization (CSIRO), 65 Brockway Road, Floreat, Underwood Avenue, WA 6014, AustraliaMichael D Abràmoff - Ophthalmology and Visual Sciences, Electrical and Computer Engineering, Biomedical Engineering, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USAR. Theodore Smith - Retinal Image Analysis Laboratory, Department of Ophthalmology, NYU School of Medicine, NY, NY 10016, USALeonard Goldschmidt - VA Palo Alto Health Care Systems, 3801 Miranda Avenue, Palo Alto, CA 94304-1290, USATien Y Wong - Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, 32 Gisborne Street, East Melbourne 3002, Australia
- Resource Type
- Journal article
- Publication Details
- Progress in Retinal and Eye Research, Vol.38, pp.20-42
- DOI
- 10.1016/j.preteyeres.2013.10.002
- PMID
- 24211245
- NLM abbreviation
- Prog Retin Eye Res
- ISSN
- 1350-9462
- eISSN
- 1873-1635
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 01/2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Ophthalmology and Visual Sciences
- Record Identifier
- 9983806252702771
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