Trainable COSFIRE filters for vessel delineation with application to retinal images

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

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

590 Citations (Scopus)


Retinal imaging provides a non-invasive opportunity for the diagnosis of several medical pathologies. The automatic segmentation of the vessel tree is an important pre-processing step which facilitates subsequent automatic processes that contribute to such diagnosis.We introduce a novel method for the automatic segmentation of vessel trees in retinal fundus images. We propose a filter that selectively responds to vessels and that we call B-COSFIRE with B standing for bar which is an abstraction for a vessel. It is based on the existing COSFIRE (Combination Of Shifted Filter Responses) approach. A B-COSFIRE filter achieves orientation selectivity by computing the weighted geometric mean of the output of a pool of Difference-of-Gaussians filters, whose supports are aligned in a collinear manner. It achieves rotation invariance efficiently by simple shifting operations. The proposed filter is versatile as its selectivity is determined from any given vessel-like prototype pattern in an automatic configuration process. We configure two B-COSFIRE filters, namely symmetric and asymmetric, that are selective for bars and bar-endings, respectively. We achieve vessel segmentation by summing up the responses of the two rotation-invariant B-COSFIRE filters followed by thresholding.The results that we achieve on three publicly available data sets (DRIVE: Se. =. 0.7655, Sp. =. 0.9704; STARE: Se. =. 0.7716, Sp. =. 0.9701; CHASE_DB1: Se. =. 0.7585, Sp. =. 0.9587) are higher than many of the state-of-the-art methods. The proposed segmentation approach is also very efficient with a time complexity that is significantly lower than existing methods.

Original languageEnglish
Pages (from-to)46-57
Number of pages12
JournalMedical image analysis
Issue number1
Publication statusPublished - 1 Jan 2015
Externally publishedYes


  • Delineation
  • Retinal image analysis
  • Trainable filters
  • Vessel segmentation


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