Automatic delineation of macular regions based on a locally defined contrast function

We consider the problem of fovea segmentation and develop a technique for delineation of macular regions based on the active-disc formalism that we recently introduced. The outlining problem is posed as one of the optimization of a locally defined contrast function using gradient-ascent maximization with respect to the affine transformation parameters that characterize the active disc. For automatic localization of the fovea and initialization of the active disc, we use the directional-derivative-based matched filter. We report validation results on three publicly available fundus image databases, amounting to a total of 1370 fundus images for automatic fovea localization and 370 fundus images for fovea segmentation and macular regions delineation. The proposed method results in a fovea localization accuracy of 100%, 92%, and 99.4%, and an average Dice similarity index of 77.78%, 67.46%, and 76.56% on DRIVE, DIARETDB0, and MESSIDOR fundus image databases, respectively. We have also developed an ImageJ plugin and an iOS App based on the proposed method.