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Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies
dc.contributor.author | Díaz González, Macarena | |
dc.contributor.author | Diez Sotelo, Marta | |
dc.contributor.author | Gómez-Ulla, Francisco | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Penedo, Manuel | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2019-12-26T10:29:01Z | |
dc.date.available | 2019-12-26T10:29:01Z | |
dc.date.issued | 2019-10-31 | |
dc.identifier.citation | Díaz, 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.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/2183/24542 | |
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.sponsorship | Instituto de Salud Carlos III; DTS18/00136 | es_ES |
dc.description.sponsorship | Ministerio de Economía y Competitividad; DPI2015-69948-R | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2016-047 | es_ES |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades; RTI2018-095894-B-I00 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | M D P I AG | es_ES |
dc.relation.uri | https://doi.org/10.3390/s19214732 | es_ES |
dc.rights | Atribución 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Optical coherence tomography by angiography | es_ES |
dc.subject | Visual acuity | es_ES |
dc.subject | Retinal vein occlusion | es_ES |
dc.subject | Artificial vision | es_ES |
dc.subject | Biomarker | es_ES |
dc.title | Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Sensors | es_ES |
UDC.volume | 19 | es_ES |
UDC.issue | 21 | es_ES |
UDC.startPage | 4732 | es_ES |
dc.identifier.doi | 10.3390/s19214732 |
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