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Glaucoma is a leading cause of blindness with permanent damage to optic nerve head. ARGALI is an automated computer-aided diagnosis system designed for glaucoma detection via optic cup-to-disc ratio assessment. It employs several methods to determine the optic cup and disc from retinal images. Optic disc detection and segmentation works have been widely reported with high success rate. However, the...
The optic disc is an important feature in the retina. We propose a method for the detection of the optic disc based on a supervised learning scheme. The method employs pixel and local neighbourhood features extracted from the ROI of a digital retinal fundus photograph. A support vector machine based classification mechanism is used to classify each image point as belonging to the cup and retina. The...
The ratio of the optic cup to disc (CDR) in retinal fundus images is one of the principal physiological characteristics in the diagnosis of glaucoma. Currently the CDR is manually determined which can be subjective and limits its use in mass screening. To automatically extract the disc, a variational level set method is proposed in this paper. For the cup, two methods making use of color intensity...
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