Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters

Nicola Strisciuglio*, George Azzopardi, Mario Vento, Nicolai Petkov

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

83 Citations (Scopus)
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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.

Original languageEnglish
Pages (from-to)1137-1149
Number of pages13
JournalMachine vision and applications
Issue number8
Publication statusPublished - 1 Nov 2016
Externally publishedYes
Event16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015 - Valletta, Malta
Duration: 2 Sep 20154 Sep 2015
Conference number: 16


  • Filters selection
  • Retinal vessels segmentation
  • Trainable filters
  • Vessel delineation


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