Abstract
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.
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Fondón, I. et al. (2012). Automatic Cup-to-Disc Ratio Estimation Using Active Contours and Color Clustering in Fundus Images for Glaucoma Diagnosis. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31298-4_46
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DOI: https://doi.org/10.1007/978-3-642-31298-4_46
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