Related Experiment Video
Updated: May 14, 2026
A Workflow to Quantitatively Determine Age-Related Macular Degeneration Lesion-Specific Variations in Fundus Autofluorescence
Published on: May 26, 2023
Automated classification of severity of age-related macular degeneration from fundus photographs
Srihari Kankanahalli1, Philippe M Burlina, Yulia Wolfson
1Applied Physics Laboratory, Johns Hopkins University, Laurel, MD 20723-6099, USA.
Purpose:
To evaluate an automated analysis of retinal fundus photographs to detect and classify severity of age-related macular degeneration compared with grading by the Age-Related Eye Disease Study (AREDS) protocol.
Methods:
Following approval by the Johns Hopkins University School of Medicine's Institution Review Board, digitized images (downloaded AT http://www.ncbi.nlm.nih.gov/gap/) of field 2 (macular) fundus photographs from AREDS obtained over a 12-year longitudinal study were classified automatically using a visual words method to compare with severity by expert graders.
Results:
Sensitivities and specificities, respectively, of automated imaging, when compared with expert fundus grading of 468 patients and 2145 fundus images are: 98.6% and 96.3% when classifying categories 1 and 2 versus categories 3 and 4; 96.1% and 96.1% when classifying categories 1 and 2 versus category 3; 98.6% and 95.7% when classifying category 1 versus category 3; and 96.0% and 94.7% when classifying category 1 versus categories 3 and 4;
Conclusions:
Development of an automated analysis for classification of age-related macular degeneration from digitized fundus photographs has high sensitivity and specificity when compared with expert graders and may have a role in screening or monitoring.
