In this paper we propose a new automatic technique for the segmentation of the Optic Disc (OD) and optic nerve head (cup) regions in retinographies for glaucoma diagnosis. It provides an estimation of the Cup-to-Disc Ratio, the main clinical indicator of the disease. OD is detected combining intensity-based, multi-tolerance and morphological methods along with the active contour technique. Cup region is obtained with a new human perception adapted version of the well-known K-means algorithm in the uniform CIE L* a* b* color space with CIE94 color difference. For comparisons, the accurate cup border obtained is rounded and soften with two different techniques: ellipse fitting and mathematical morphology along with Gaussian Smoothing. The proposed method with both rounding steps has been tested in a database of 55 images and compared with the ground truth provided by an expert ophthalmologist. Both, OD and cup region, were satisfactory localized, achieving a mean error of 0.14 for ellipse fitting and 0.13 for morphology. The algorithm proposed seems to be a robust and reliable tool worthy to be included in any CAD system for glaucoma screening programs. © 2012 Springer-Verlag.
CITATION STYLE
Fondón, I., Núñez, F., Tirado, M., Jiménez, S., Alemany, P., Abbas, Q., … Acha, B. (2012). Automatic cup-to-disc ratio estimation using active contours and color clustering in fundus images for glaucoma diagnosis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7325 LNCS, pp. 390–399). https://doi.org/10.1007/978-3-642-31298-4_46
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