Retinal vessel segmentation via structure tensor coloring and anisotropy enhancement

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dc.authorid0000-0002-0867-5518en_US
dc.contributor.authorNergiz, Mehmet
dc.contributor.authorAkın, Mehmet
dc.date.accessioned2024-01-29T10:58:27Z
dc.date.available2024-01-29T10:58:27Z
dc.date.issued2017en_US
dc.departmentDicle Üniversitesi, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractRetinal vessel segmentation is one of the preliminary tasks for developing diagnosis software systems related to various retinal diseases. In this study, a fully automated vessel segmentation system is proposed. Firstly, the vessels are enhanced using a Frangi Filter. Afterwards, Structure Tensor is applied to the response of the Frangi Filter and a 4-D tensor field is obtained. After decomposing the Eigenvalues of the tensor field, the anisotropy between the principal Eigenvalues are enhanced exponentially. Furthermore, this 4-D tensor field is converted to the 3-D space which is composed of energy, anisotropy and orientation and then a Contrast Limited Adaptive Histogram Equalization algorithm is applied to the energy space. Later, the obtained energy space is multiplied by the enhanced mean surface curvature of itself and the modified 3-D space is converted back to the 4-D tensor field. Lastly, the vessel segmentation is performed by using Otsu algorithm and tensor coloring method which is inspired by the ellipsoid tensor visualization technique. Finally, some post-processing techniques are applied to the segmentation result. In this study, the proposed method achieved mean sensitivity of 0.8123, 0.8126, 0.7246 and mean specificity of 0.9342, 0.9442, 0.9453 as well as mean accuracy of 0.9183, 0.9442, 0.9236 for DRIVE, STARE and CHASE_DB1 datasets, respectively. The mean execution time of this study is 6.104, 6.4525 and 18.8370 s for the aforementioned three datasets respectively.en_US
dc.identifier.citationNergiz, M. ve Akın, M. (2017). Retinal vessel segmentation via structure tensor coloring and anisotropy enhancement. Symmetry, 9(11), 1-18.en_US
dc.identifier.endpage18en_US
dc.identifier.issn2073-8994
dc.identifier.issue11en_US
dc.identifier.scopusScopusIdYok
dc.identifier.scopusqualityQ1
dc.identifier.startpage1en_US
dc.identifier.urihttps://www.mdpi.com/2073-8994/9/11/276
dc.identifier.urihttps://hdl.handle.net/11468/13298
dc.identifier.volume9en_US
dc.identifier.wosWOS:000416805700030
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorNergiz, Mehmet
dc.institutionauthorAkın, Mehmet
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofSymmetry
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAnisotropy enhancementen_US
dc.subjectFrangi vesselness filteren_US
dc.subjectRetinal blood vesselsen_US
dc.subjectSegmentationen_US
dc.subjectStructure tensoren_US
dc.subjectTensor visualizationen_US
dc.titleRetinal vessel segmentation via structure tensor coloring and anisotropy enhancementen_US
dc.titleRetinal vessel segmentation via structure tensor coloring and anisotropy enhancement
dc.typeArticleen_US

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