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dc.contributor.authorMoura, Joaquim de
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorRouco, J.
dc.contributor.authorPenedo, Manuel
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2024-06-07T11:32:55Z
dc.date.available2024-06-07T11:32:55Z
dc.date.issued2017-06
dc.identifier.citationMoura, J. de, Novo, J., Rouco, J., Penedo, M.G., Ortega, M. (2017). Automatic Detection of Blood Vessels in Retinal OCT Images. In: Ferrández Vicente, J., Álvarez-Sánchez, J., de la Paz López, F., Toledo Moreo, J., Adeli, H. (eds) Biomedical Applications Based on Natural and Artificial Computing. IWINAC 2017. Lecture Notes in Computer Science, vol 10338. Springer, Cham. https://doi.org/10.1007/978-3-319-59773-7_1es_ES
dc.identifier.urihttp://hdl.handle.net/2183/36838
dc.description7th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017 Coruña 19 June 2017 - 23 June 2017es_ES
dc.descriptionThis version of the article has been accepted for publication, after peer review (when applicable) 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/10.1007/978-3-319-59773-7_1es_ES
dc.description.abstract[Abstract]: The eye is a non-invasive window where clinicians can observe and study in vivo the retinal vasculature, allowing the early detection of different relevant pathologies. In this paper, we present a complete methodology for the automatic vascular detection in retinal OCT images. To achieve this, we analyse the intensity profiles between representative layers of the retina, layers that are previously segmented. Then, we propose the use of two threshold-based strategies for vessel detection, a fixed and an adaptive approach. Both methods have been tested and validated with 128 OCT images, that include 560 vessels that were labelled by an ophthalmologist. The approaches provided satisfactory results, facilitating the doctors’ work and allowing better analysis and treatment of vascular diseases.es_ES
dc.description.sponsorshipThis work is supported by the Instituto de Salud Carlos III of the Spanish Government and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects.es_ES
dc.language.isoenges_ES
dc.publisherSpringer Verlages_ES
dc.relationinfo: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 VISIÓNes_ES
dc.relationinfo: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 CLÍNICOSes_ES
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10338es_ES
dc.relation.urihttps://doi.org/10.1007/978-3-319-59773-7_1es_ES
dc.rights© 2017 Springer International Publishing AG.es_ES
dc.subjectComputer-aidedes_ES
dc.subjectDiagnosises_ES
dc.subjectOptical coherence tomographyes_ES
dc.subjectRetinal imaginges_ES
dc.subjectVessel detectiones_ES
dc.titleAutomatic Detection of Blood Vessels in Retinal OCT Imageses_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleBiomedical Applications Based on Natural and Artificial Computinges_ES
dc.identifier.doi10.1007/978-3-319-59773-7_1
UDC.conferenceTitleIWINAC 2017es_ES


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