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