Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/6023
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dc.contributor.authorDashtbozorg,Ben
dc.contributor.authorAna Maria Mendonçaen
dc.contributor.authorAurélio Campilhoen
dc.date.accessioned2018-01-13T18:36:21Z-
dc.date.available2018-01-13T18:36:21Z-
dc.date.issued2013en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/6023-
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-642-39094-4_60en
dc.description.abstractThe Arteriolar-to-Venular Ratio (AVR) is a well known index for the diagnosis of diseases such as diabetes, hypertension or cardiovascular pathologies. This paper presents a fully automatic AVR estimation method which uses a graph-based artery/vein classification approach to classify the retinal vessels by a combination of structural information taken from the vasculature graph with intensity features from the original color image. This method was evaluated on the images of the INSPIRE-AVR dataset. The mean error and the correlation coefficient of obtained results with respect to the reference AVR values were identical to the ones obtained by the second observer using a semi-automated system, which demonstrate the potential of the herein proposed solution for clinical application.en
dc.languageengen
dc.relation6381en
dc.relation6071en
dc.rightsinfo:eu-repo/semantics/embargoedAccessen
dc.titleAutomatic Estimation of the Arteriolar-to-Venular Ratio in Retinal Images Using a Graph-Based Approach for Artery/Vein Classificationen
dc.typeconferenceObjecten
dc.typePublicationen
Appears in Collections:Non INESC TEC publications - Articles in International Conferences

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