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This work proposes a method for the detection of glaucoma using fundus image based on the optic disc and cup size. The ratio of the optic cup to disc (CDR) in retinal fundus images is one of the primary physiological parameter for the diagnosis of glaucoma. Using SVM classifier the dataset is trained. The CDR values are considered as features for the prediction. Also, the advantages of using electriucal stimulation for the treatment of glaucom are prosed in this study. The mechanism underlying the electrical stimulation for the positive effects are outlined in connection with their effects on increased production of neurotrophic agents. Therefore through work, we aim to provide insight on the applications CDR and the advantages of electrical stimulation and its importance as a potential therapy for improving vision and treating various eye diseases.
 U. Rajendra Acharya, Sumeet Dua, Xian Du,, Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features, IEEE Transactions On Information Technology In Biomedicine, May 2011, pp 449-455.