A Neural Network-based Retinal Imaging Interface for Optic Disc Localization in Ophthalmic Analyses

An automatic detection of the position of Optic Disc (OD) is a fundamental step in the analysis of retinal images, due to the fact that precise determinations about the localization of Optic Nerve and OD in retinal images reveals necessary to examine the severity of some diseases. Changes in the OD often indicate a pathologic progression. On the basis of multiple pixel determinations of a multiple Processor on captured fundus images, in this work a NN-based Positioning Interface, constituted by a Retinal Imaging System, a Neural Validity Classifier and a Positioning Processor for an accurate localization of the Reference point of OD, is presented. More in detail, the locations of multiple candidates are accurately validated by synthesizing a Neural Network behaving as a Classifier of Validity for regular/abnormal candidate reference points. Then, a Positioning Processor, which considers only validated midpoints, adopts the most suitable point as the Reference point of the OD for subsequent ophthalmic analyses. Simulation results are reported on selected fundus oculi images.