article Open Access
Automatic detection of diabetic retinopathy using an artificial neural network: a screening tool.
British Journal of Ophthalmology · 1996 · Vol. 80(11) · pp. 940–944
Graeme Gardner✉(University of Glasgow)Daniel P. Keating(University of Glasgow)Tom H. Williamson(University of Glasgow)Alex Elliott(University of Glasgow)
Abstract
Detection of vessels, exudates, and haemorrhages was possible, with success rates dependent upon preprocessing and the number of images used in training. When compared with the ophthalmologist, the network achieved good accuracy for the detection of diabetic retinopathy. The system could be used as an aid to the screening of diabetic patients for retinopathy.
Retinal Imaging and AnalysisRetinal Diseases and TreatmentsArtificial Intelligence in HealthcareDiabetic retinopathyMedicineFundus (uterus)PreprocessorRetinopathyArtificial intelligenceArtificial neural networkOphthalmologyRetinalRetina
MeSH terms
Diabetic RetinopathyFundus OculiHumansSensitivity and SpecificitySoftware ValidationSingle-Blind MethodNeural Networks, Computer
Citations
505
FWCI
2.34
field-weighted impact
References
24
Percentile
87%
vs. same field & year
Citations per year
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