Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels.
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.
Hoover
Adam
A
Electrical and Computer Engineering Department, Clemson University, Clemson SC 29634-0915, USA. ahoover@clemson.edu
Goldbaum
Michael
M
D000465:Algorithms; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009887:Ophthalmoscopy / Q000379:methods*; D009900:Optic Nerve / Q000473:pathology*; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012160:Retina / Q000473:pathology; D012164:Retinal Diseases / Q000473:pathology*; D012171:Retinal Vessels / Q000473:pathology*; D012680:Sensitivity and Specificity