Graph-based minimal path tracking in the skeleton of the retinal vascular network

This paper presents a semi-automatic framework for minimal path tracking in the skeleton of the retinal vascular network. The method is based on the graph structure of the vessel network. The vascular network is represented based on the skeleton of the available segmented vessels and using an undirected graph. Significant points on the skeleton are considered nodes of the graph, while the edge of the graph is represented by the vessel segment linking two neighboring nodes. The graph is represented then in the form of a connectivity matrix, using a novel method for defining vertex connectivity. Dijkstra and Floyd-Warshall algorithms are applied for detection of minimal paths within the graph. The major contribution of this work is the accurate detection of significant points and the novel definition of vertex connectivity based on a new neighborhood system adopted. The qualitative performance of our method evaluated on the publicly available DRIVE database shows useful results for further purposes.