Blood vessels extraction and classification into arteries and veins in retinal images

Many retinal diseases are characterized by changes in retinal vessels. The retina vascular structure consists of two kinds of vessels: arteries and veins. An important symptom for Diabetic Retinopathy DR is irregularly wide veins, leading to an unusually low ratio of the average diameter of arteries to veins (AVR). In this paper, we present an approach to separate arteries and veins based on a segmentation and neural classification method. Blood vessels are segmented using two-dimensional matched filters, which derived from Gaussian functions. We used feature vectors based on vessel profile extraction for each segment. The obtained features will be introduced as the input vector of a Multi-Layer Perceptron (MLP); to classify the vessel into arteries and veins ones. Our approach achieves 95.32% correctly classified vessel pixels classification.