A modular supervised algorithm for vessel segmentation in red-free retinal images.

In this paper, a supervised algorithm for vessel segmentation in red-free images of the human retina is proposed. The algorithm is modular and made up of two fundamental blocks. The optimal values of two algorithm parameters are found out by maximizing proper measures of performances (MOPs) able to evaluate from a quantitative point of view the results provided by the proposed algorithm.