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Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels

IEEE Transactions on Medical Imaging · 2003 · Vol. 22(8) · pp. 951–958
Adam HooverMichael H. Goldbaum

Abstract

We describe an automated method to locate the optic nerve in images of the ocular fundus. Our method uses a novel algorithm we call fuzzy convergence to determine the origination of the blood vessel network. We evaluate our method using 31 images of healthy retinas and 50 images of diseased retinas, containing such diverse symptoms as tortuous vessels, choroidal neovascularization, and hemorrhages that completely obscure the actual nerve. On this difficult data set, our method achieved 89% correct detection. We also compare our method against three simpler methods, demonstrating the performance improvement. All our images and data are freely available for other researchers to use in evaluating related methods.

Retinal Imaging and AnalysisGlaucoma and retinal disordersDigital Imaging for Blood DiseasesFundus (uterus)Computer scienceOptic nerveArtificial intelligenceComputer visionConvergence (economics)Fuzzy logicData setBlood vesselRetinal

MeSH terms

AlgorithmsHumansImage EnhancementImage Interpretation, Computer-AssistedOphthalmoscopyOptic NervePattern Recognition, AutomatedRetinaRetinal DiseasesRetinal VesselsSensitivity and SpecificityReproducibility of ResultsFuzzy Logic
Citations
794
FWCI
9.92
field-weighted impact
References
26
Percentile
98%
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Citations per year
References
Image processing, analysis and machine vision
Neurocomputing · 1994 · 1,820 citations
Numerical recipes in C: the art of scientific computing
Choice Reviews Online · 1993 · 17,990 citations
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