Title :
Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels
Author :
Hoover, Adam ; Goldbaum, Michael
Author_Institution :
Dept. of Electr. & Comput. Eng., Clemson Univ., SC, USA
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.
Keywords :
biomedical optical imaging; blood vessels; brightness; convergence; diseases; eye; fuzzy set theory; image segmentation; medical image processing; automated method; blood vessels; choroidal neovascularization; diseased retinas; fuzzy convergence; hemorrhages; ocular fundus; optic nerve; optical image processing; performance improvement; retinal image; tortuous vessels; Biomedical imaging; Biomedical optical imaging; Blood vessels; Brightness; Convergence; Lesions; Optical distortion; Optical imaging; Retina; Shape; Algorithms; Fuzzy Logic; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Ophthalmoscopy; Optic Nerve; Pattern Recognition, Automated; Reproducibility of Results; Retina; Retinal Diseases; Retinal Vessels; Sensitivity and Specificity;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2003.815900