An Automatic Computer Aided Diagnostic System for the Analysis of Glaucoma Using Super pixel Classification and Clustering Methods
نویسنده
چکیده
Glaucoma is a chronic eye disease that leads to vision loss. As it cannot be cured, detecting the disease in time is important. This research proposes optic disc and optic cup segmentation using superpixel classification for glaucoma screening. It uses the 2D fundus images. In optic disc segmentation, clustering algorithms are used to classify each superpixel as disc or nondisc. For optic cup segmentation, in addition to the clustering algorithms, the gabor filter is also included into the feature space to boost the performance. The segmented optic disc and optic cup are then used to compute the cup to disc ratio for glaucoma screening. The Cup to Disc Ratio (CDR) of the color retinal fundus camera image is the primary identifier to confirm Glaucoma for a given patient.
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