Automated segmentation of optic disc region on retinal fundus photographs: Comparison of contour modeling and pixel classification methods.
The automatic determination of the optic disc area in retinal fundus images can be useful for calculation of the cup-to-disc (CD) ratio in the glaucoma screening. We compared three different methods that employed active contour model (ACM), fuzzy c-mean (FCM) clustering, and artificial neural network (ANN) for the segmentation of the optic disc regions. The results of these methods were evaluated using new databases that included the images captured by different camera systems. The average measures of overlap between the disc regions determined by an ophthalmologist and by using the ACM (0.88 and 0.87 for two test datasets) and ANN (0.88 and 0.89) methods were slightly higher than that by using FCM (0.86 and 0.86) method. These results on the unknown datasets were comparable with those of the resubstitution test; this indicates the generalizability of these methods. The differences in the vertical diameters, which are often used for CD ratio calculation, determined by the proposed methods and based on the ophthalmologist's outlines were even smaller than those in the case of the measure of overlap. The proposed methods can be useful for automatic determination of CD ratios.
Muramatsu
Chisako
C
Department of Intelligent Image Information, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1194, Japan. chisa@fjt.info.gifu-u.ac.jp
Nakagawa
Toshiaki
T
Sawada
Akira
A
Hatanaka
Yuji
Y
Hara
Takeshi
T
Yamamoto
Tetsuya
T
Fujita
Hiroshi
H
D000465:Algorithms; D016000:Cluster Analysis; D016208:Databases, Factual; D005654:Fundus Oculi; D017143:Fuzzy Logic; D005901:Glaucoma / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D009898:Optic Disk / Q000473:pathology*; D010781:Photography / Q000379:methods*