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A novel system for the vascular tree identification and the quantitative estimation of arteriolar venular ratio clinical index in retinal fundus images is presented. The system is composed of a module for automatic vascular tracking, an interactive editing interface to correct errors and set the required parameters of analysis, and a module for the computation of clinical indexes. The system was organized as a client-server structure to allow clinicians and researchers from all over the world to work remotely. The system was evaluated by three graders analyzing 30 fundus images. The evaluation of the Pearson's correlation coefficient and -value of a paired -test for each pair of graders demonstrates the high reproducibility of the measures provided by the system.
Date of Publication: March 2011