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dc.contributor.authorDíez Sotelo, Marta
dc.contributor.authorDíaz, M.
dc.contributor.authorAbraldes Lopez-Veiga, Maximino 
dc.contributor.authorGómez-Ulla, F.
dc.contributor.authorG Penedo, M.
dc.contributor.authorOrtega, M.
dc.date.accessioned2021-10-04T09:38:27Z
dc.date.available2021-10-04T09:38:27Z
dc.date.issued2019
dc.identifier.issn2077-0383
dc.identifier.otherhttps://www.ncbi.nlm.nih.gov/pubmed/31547127es
dc.identifier.urihttp://hdl.handle.net/20.500.11940/15424
dc.description.abstractThe assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.en
dc.language.isoeng
dc.rightsAtribución 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.meshRetinal Vein Occlusion*
dc.titleA Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiographyes
dc.typeArtigoes
dc.authorsophosDíez-Sotelo, M.
dc.authorsophosDíaz, M.
dc.authorsophosAbraldes, M.
dc.authorsophosGómez-Ulla, F.
dc.authorsophosG Penedo, M.
dc.authorsophosOrtega, M.
dc.identifier.doi10.3390/jcm8101515
dc.identifier.pmid31547127
dc.identifier.sophos30677
dc.issue.number10es
dc.journal.titleJournal of Clinical Medicinees
dc.organizationServizo Galego de Saúde::Estrutura de Xestión Integrada (EOXI)::EOXI de Santiago de Compostela - Complexo Hospitalario Universitario de Santiago de Compostela::Análise clínicos
dc.page.initial1515es
dc.relation.publisherversionhttps://res.mdpi.com/d_attachment/jcm/jcm-08-01515/article_deploy/jcm-08-01515-v2.pdf
dc.rights.accessRightsopenAccess
dc.subject.keywordCHUS
dc.typefidesArtículo Científico (incluye Original, Original breve, Revisión Sistemática y Meta-análisis)
dc.typesophosArtículo Original
dc.volume.number8es


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