Hyperspectral Image Segmentation of Retinal Vasculature, Optic Disc and Macula

Abstract

The most common approach for retinal imaging is the eye fundus photography which usually results in RGB images. Recent studies show that the additional spectral information provides useful features for automatic retinal image analysis. The current work extends recent research on the joint segmentation of retinal vasculature, optic disc and macula which often appears in different retinal image analysis tasks. Fully convolutional neural networks are utilized to solve the segmentation problem. It is shown that the network architectures can be effectively modified for the spectral data and the utilization of spectral information provides moderate improvements in retinal image segmentation.