A Fast and Reliable Method for Early Detection of Glaucoma

Glaucoma is a serious ocular disease and leads to blindness if it is not detected and treated. Hence, it is important to develop various detection techniques to assist clinicians to diagnose at early stage. In this paper, we propose methods for an automatic CDR determination. The optic disc region is segmented by using active contour model and optic cup is segmented by using fuzzy c mean clustering. The segmented contour of optic disc and optic cup has been smoothened by circular fitting and CDR is calculated for 50 normal images and 100 fundus images. The ISNT (Inferior Superior Nasal Temporal) ratios for the neuro retinal rim area and the blood vessels in the optic disc region are considered. The blood vessels are segmented by morphological method and the neuro retinal rim (NRR) is the area between the optic disc and optic cup. For these two features, values of ISNT ratio are computed. The features namely CDR, ISNT ratio for blood vessels NRR area and texture features are used for classifying by Support Vector Machine (SVM). The results show sensitivity, specificity and accuracy of SVM classifier as 96%, 93.33% and 95.38% respectively.

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