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dc.contributor.authorChamoso Santos, Pablo 
dc.contributor.authorGarcía Ortiz, Luis 
dc.contributor.authorRecio Rodríguez, José Ignacio 
dc.contributor.authorGómez Marcos, Manuel Ángel 
dc.date.accessioned2017-09-06T09:16:21Z
dc.date.available2017-09-06T09:16:21Z
dc.date.issued2014
dc.identifier.citation8th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2014) Advances in Intelligent Systems and Computing. Volumen 294, pp. 21-30.
dc.identifier.isbn978-3-319-07580-8 (Print) / 978-3-319-07581-5 (Online)
dc.identifier.issn2194-5357
dc.identifier.urihttp://hdl.handle.net/10366/135080
dc.description.abstractRecent studies have found retinal vessel caliber to be related to the risk of hypertension, left ventricular hypertrophy, metabolic syndrome, stroke and others coronary artery diseases. The vascular system in the human retina is easily perceived in its natural living state by the use of a retinal camera. Nowadays, there is general experimental agreement on the analysis of the patterns of the retinal blood vessels in the normal human retina. The development of automated tools designed to improve performance and decrease interobserver variability, therefore, appears necessary. This paper presents a study focused on developing a technological platform specialized in assessing retinal vessel caliber and describing the relationship of the results obtained to cardiovascular risk.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titlePlatform Image Processing Applied to the Study of Retinal Vessels
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported