Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies

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UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvGrupo de Visión Artificial e Recoñecemento de Patróns (VARPA)es_ES
UDC.issue21es_ES
UDC.journalTitleSensorses_ES
UDC.startPage4732es_ES
UDC.volume19es_ES
dc.contributor.authorDíaz González, Macarena
dc.contributor.authorDíez Sotelo, Marta
dc.contributor.authorGómez-Ulla, Francisco
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorPenedo, Manuel
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2019-12-26T10:29:01Z
dc.date.available2019-12-26T10:29:01Z
dc.date.issued2019-10-31
dc.description.abstract[Abstract] Optical Coherence Tomography Angiography (OCTA) constitutes a new non-invasive ophthalmic image modality that allows the precise visualization of the micro-retinal vascularity that is commonly used to analyze the foveal region. Given that there are many systemic and eye diseases that affect the eye fundus and its vascularity, the analysis of that region is crucial to diagnose and estimate the vision loss. The Visual Acuity (VA) is typically measured manually, implying an exhaustive and time-consuming procedure. In this work, we propose a method that exploits the information of the OCTA images to automatically estimate the VA with an accurate error of 0.1713.es_ES
dc.description.sponsorshipInstituto de Salud Carlos III; DTS18/00136es_ES
dc.description.sponsorshipMinisterio de Economía y Competitividad; DPI2015-69948-Res_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2016-047es_ES
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades; RTI2018-095894-B-I00es_ES
dc.identifier.citationDíaz, M.; Díez-Sotelo, M.; Gómez-Ulla, F.; Novo, J.; Penedo, M.F.G.; Ortega, M. Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies. Sensors 2019, 19, 4732.es_ES
dc.identifier.doi10.3390/s19214732
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2183/24542
dc.language.isoenges_ES
dc.publisherM D P I AGes_ES
dc.relation.urihttps://doi.org/10.3390/s19214732es_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectOptical coherence tomography by angiographyes_ES
dc.subjectVisual acuityes_ES
dc.subjectRetinal vein occlusiones_ES
dc.subjectArtificial visiones_ES
dc.subjectBiomarkeres_ES
dc.titleAutomatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographieses_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication0fcd917d-245f-4650-8352-eb072b394df0
relation.isAuthorOfPublicationfd42beb9-8d01-41bd-a634-4e86e2c69597
relation.isAuthorOfPublication1fb98665-ea68-4cd3-a6af-83e6bb453581
relation.isAuthorOfPublication.latestForDiscovery0fcd917d-245f-4650-8352-eb072b394df0

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