Journal Paper

  

Nicola Strisciuglio, George Azzopardi, Mario Vento, and Nicolai Petkov, “Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters” Machine Vision and Applications, doi: 10.1007/s00138-016-0781-7, 2016.
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Abstract

The inspection of retinal fundus images allows medical doctors to diagnose various pathologies. Computer-aided diagnosis systems can be used to assist in this process. As a first step, such systems delineate the vessel tree from the background. We propose a method for the delineation of blood vessels in retinal images that is effective for vessels of different thickness. In the proposed method, we employ a set of B-COSFIRE filters selective for vessels and vessel-endings. Such a set is determined in an automatic selection process and can adapt to different applications. We compare the performance of different selection methods based upon machine learning and information theory. The results that we achieve by performing experiments on two public benchmark data sets, namely DRIVE and STARE, demonstrate the effectiveness of the proposed approach.

Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, the Netherlands