Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/26329
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dc.contributor.authorStrisciuglio, Nicola-
dc.contributor.authorVento, Mario-
dc.contributor.authorPetkov, Nicolai-
dc.contributor.authorAzzopardi, George-
dc.date.accessioned2018-02-02T07:27:18Z-
dc.date.available2018-02-02T07:27:18Z-
dc.date.issued2016-
dc.identifier.citationStrisciuglio, N., Azzopardi, G., Vento, M., & Petkov, N. (2016). Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters. Machine Vision and Applications, 27(8), 1137-1149.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar//handle/123456789/26329-
dc.description.abstractThe 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 vesselendings. 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.en_GB
dc.language.isoenen_GB
dc.publisherSpringeren_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectImage processingen_GB
dc.subjectPattern recognition systemsen_GB
dc.subjectRetina -- Imagingen_GB
dc.titleSupervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filtersen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1007/s00138-016-0781-7-
dc.publication.titleMachine Vision and Applicationsen_GB
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