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dc.contributor.authorBaamonde, Sergio
dc.contributor.authorMoura, Joaquim de
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2024-06-18T10:35:52Z
dc.date.available2024-06-18T10:35:52Z
dc.date.issued2017-05-18
dc.identifier.citationBaamonde, S., de Moura, J., Novo, J., Ortega, M. (2017). Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science, vol 10305. Springer, Cham. https://doi.org/10.1007/978-3-319-59153-7_20es_ES
dc.identifier.isbn978-3-319-59152-0
dc.identifier.isbn978-3-319-59153-7
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/2183/37071
dc.descriptionThe conference was held in Cadiz, Spain, June 14-16, 2017.es_ES
dc.description©2017 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/10.1007/978-3-319-59153-7_20es_ES
dc.description.abstract[Absctract]: This work presents a novel approach for automatic detection of the epiretinal membrane in Optical Coherence Tomography (OCT) images. A tool able to detect this pathology is very valued since it can prevent further ocular damage by doing an early detection. This approach is based in the location of the inner limiting membrane (ILM) layers of the retina. Then, the detected locations are classified using a local-feature based vector in order to determine presence of the membrane. Different tests are run and compared to establish the appropriateness of the approach as well as its practical validity.es_ES
dc.description.sponsorshipThis work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union throug 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.es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_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.relationinfo: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 MAQUINAes_ES
dc.relation.urihttps://doi.org/10.1007/978-3-319-59153-7_20es_ES
dc.subjectEpiretinal membranees_ES
dc.subjectRetinal layerses_ES
dc.subjectMedical imaginges_ES
dc.subjectOptical coherence tomographyes_ES
dc.titleAutomatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patternses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleAdvances in Computational Intelligence: 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cadiz, Spain, June 14-16, 2017, Proceedings, Part I ( Lecture Notes in Computer Science, LNCS)es_ES
UDC.volume10305es_ES
UDC.startPage222es_ES
UDC.endPage235es_ES
UDC.conferenceTitle14th International Work-Conference on Artificial Neural Networks, IWANN 2017es_ES


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