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Automatic Retinal Vascularity Identification and Artery/Vein Classification Using Near-Infrared Reflectance Retinographies
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.contributor.author | Barreira, Noelia | |
dc.contributor.author | Charlón, Pablo | |
dc.date.accessioned | 2024-06-19T08:53:42Z | |
dc.date.available | 2024-06-19T08:53:42Z | |
dc.date.issued | 2019-01 | |
dc.identifier.citation | Moura, J. de, Novo, J., Ortega, M., Barreira, N., Charlón, P. (2019). Automatic Retinal Vascularity Identification and Artery/Vein Classification Using Near-Infrared Reflectance Retinographies. In: Cláudio, A., et al. Computer Vision, Imaging and Computer Graphics – Theory and Applications. VISIGRAPP 2017. Communications in Computer and Information Science, vol 983. Springer, Cham. https://doi.org/10.1007/978-3-030-12209-6_13 | es_ES |
dc.identifier.isbn | 978-3-030-12208-9 | |
dc.identifier.isbn | 978-3-030-12209-6 | |
dc.identifier.issn | 1865-0929 | |
dc.identifier.issn | 1865-0937 | |
dc.identifier.uri | http://hdl.handle.net/2183/37128 | |
dc.description | The conference was held in Porto, Portugal, February 27 – March 1, 2017. | es_ES |
dc.description | ©2019 This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-030-12209-6_13 | es_ES |
dc.description.abstract | [Absctract]: The retinal microcirculation structure is commonly used as an important source of information in many medical specialities for the diagnosis of relevant diseases such as, for reference, hypertension, arteriosclerosis, or diabetes. Also, the evaluation of the cerebrovascular and cardiovascular disease progression could be performed through the identification of abnormal signs in the retinal vasculature architecture. Given that these alterations affect differently the artery and vein vascularities, a precise characterization of both blood vessel types is also crucial for the diagnosis and treatment of a significant variety of retinal and systemic pathologies. In this work, we present a fully automatic method for the retinal vessel identification and classification in arteries and veins using Optical Coherence Tomography scans. In our analysis, we used a dataset composed by 30 near-infrared reflectance retinography images from different patients, which were used to test and validate the proposed method. In particular, a total of 597 vessel segments were manually labelled by an expert clinician, being used as groundtruth for the validation process. As result, this methodology achieved a satisfactory performance in the complex issue of the retinal vessel tree identification and classification. | es_ES |
dc.description.sponsorship | This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund - ERDF) and the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016-2019, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. ED431C 2016-047. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2016-047 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PI14%2F02161/ES/DESARROLLO DE UN SISTEMA AUTOMÁTICO PARA EL CÁLCULO Y VISUALIZACIÓN DE PROPIEDADES ANATÓMICAS DE LA RETINA EN SD-OCT Y SU CORRELACIÓN CON ANÁLISIS FUNCIONALES HETEROGÉNEOS DE LA VISIÓN | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DTS15%2F00153/ES/SIRIUS - SISTEMA DE ANÁLISIS DE MICROCIRCULACIÓN RETINIANA: EVALUACIÓN MULTIDISCIPLINAR E INTEGRACIÓN EN PROTOCOLOS CLÍNICOS | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2015-69948-R/ES/IDENTIFICACION Y CARACTERIZACION DEL EDEMA MACULAR DIABETICO MEDIANTE ANALISIS AUTOMATICO DE TOMOGRAFIAS DE COHERENCIA OPTICA Y TECNICAS DE APRENDIZAJE MAQUINA | es_ES |
dc.relation.uri | https://doi.org/10.1007/978-3-030-12209-6_13 | es_ES |
dc.subject | Retinal imaging | es_ES |
dc.subject | Vascular tree | es_ES |
dc.subject | Segmentation | es_ES |
dc.subject | Artery/vein classification | es_ES |
dc.title | Automatic Retinal Vascularity Identification and Artery/Vein Classification Using Near-Infrared Reflectance Retinographies | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Computer Vision, Imaging and Computer Graphics – Theory and Applications (Communications in Computer and Information Science, CCIS) | es_ES |
UDC.volume | 983 | es_ES |
UDC.startPage | 262 | es_ES |
UDC.endPage | 278 | es_ES |
UDC.conferenceTitle | 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics, VISIGRAPP 2017 | es_ES |