Automated Analysis of Retinal Images

We describe a method for segmenting retinal images using positions of blood vessels supplying the retina. The image is tessellated into irregularly shaped primary regions which are bounded by vessels, chains of microaneurysms, edges, etc. Boundaries are classified into groups using a trained set of grey level models. We define a process of merging primary regions into large patches using image properties such as texture and intensity, and semantic interpretations of boundaries and their measured properties. The method which makes extensive use of morphological processing depends on a limited number of parameters which have natural physical interpretations.