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In this work, we have presented a novel method for detection of retinal imagefeatures, the optic disc and the fovea, from colour fundus photographs ofdilated eyes for Computer-aided Diagnosis(CAD) system. A saliency map basedmethod was used to detect the optic disc followed by an unsupervisedprobabilistic Latent Semantic Analysis for detection validation. The validationconcept is based on distinct vessels structures in the optic disc. By using theclinical information of standard location of the fovea with respect to theoptic disc, the macula region is estimated. Accuracy of 100\% detection isachieved for the optic disc and the macula on MESSIDOR and DIARETDB1 and 98.8\%detection accuracy on STARE dataset.

An Unsupervised Method for Detection and Validation of The Optic Disc and The Fovea