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.
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1 Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands; Department of Computer Engineering and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano, Italy
2 Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands; Intelligent Computer Systems, University of Malta, Msida, Malta
3 Department of Computer Engineering and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano, Italy
4 Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands