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.
developed an ImageJ plugin and an iOS App based on theproposed method.

Published in: 2017 IEEE International Conference on Image Processing (ICIP)

Date of Conference: 17-20 Sept. 2017

Date Added to IEEE Xplore: 22 February 2018

Electronic ISSN: 2381-8549

INSPEC Accession Number: 17564057

DOI: 10.1109/ICIP.2017.8296504Publisher: IEEE

Conference Location: Beijing, China