dc.contributor.author | Díaz González, Macarena | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Penedo, Manuel | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2024-06-27T07:34:28Z | |
dc.date.available | 2024-06-27T07:34:28Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | M. Díaz, J. Novo, M. G. Penedo, y M. Ortega, «Automatic extraction of vascularity measurements using OCT-A images», Procedia Computer Science, vol. 126, pp. 273-281, 2018, doi: 10.1016/j.procs.2018.07.261. | es_ES |
dc.identifier.issn | 1877-0509 | |
dc.identifier.uri | http://hdl.handle.net/2183/37453 | |
dc.description | The conference was held in Belgrade, Serbia, 3-5 September 2018. | es_ES |
dc.description.abstract | [Absctract]: Optical Coherence Tomography Angiography (OCT-A) represents a new modality of ophthalmological imaging that stands out for being a non-invasive capture technique that facilitates the analysis of the vascular characteristics of the eye fundus. In this paper, we propose a complete automatic methodology that identifies the vascular and avascular zones in OCT-A images, quantifying each one of them for their posterior use in clinical analyses and diagnostic processes. To achieve this, we firstly intensify the vascular characteristics to facilitate the posterior extraction. Then, a set of image processing techniques are combined to differentiate both vascular and avascular regions and, finally, measure their representative parameters. The proposed methodology was tested on a set of images that were marked by an expert ophthalmologist, being used as reference in the validation of the method. The proposed approach presented satisfactory results in the validation experiments with the vascular and avascular measurements, demonstrating their utility for the diagnosis and monitoring of different vascular diseases that are frequently analysed through the retinal microcirculation. | es_ES |
dc.description.sponsorship | This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 research projects and by the Ministerio de Economía y
Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received
financial support from the European Union (European Regional Development Fund - ERDF) and the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016-2019, Ref. ED431G/01; and Grupos de Referencia
Competitiva, Ref. ED431C 2016-047. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2016-047 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PI14%2F02161/ES/DESARROLLO DE UN SISTEMA AUTOMÁTICO PARA EL CÁLCULO Y VISUALIZACIÓN DE PROPIEDADES ANATÓMICAS DE LA RETINA EN SD-OCT Y SU CORRELACIÓN CON ANÁLISIS FUNCIONALES HETEROGÉNEOS DE LA VISIÓN | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DTS15%2F00153/ES/SIRIUS - SISTEMA DE ANÁLISIS DE MICROCIRCULACIÓN RETINIANA: EVALUACIÓN MULTIDISCIPLINAR E INTEGRACIÓN EN PROTOCOLOS CLÍNICOS | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2015-69948-R/ES/IDENTIFICACION Y CARACTERIZACION DEL EDEMA MACULAR DIABETICO MEDIANTE ANALISIS AUTOMATICO DE TOMOGRAFIAS DE COHERENCIA OPTICA Y TECNICAS DE APRENDIZAJE MAQUINA | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.procs.2018.07.261 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Computer-aided diagnosis | es_ES |
dc.subject | Image Segmentation | es_ES |
dc.subject | Retinal imaging | es_ES |
dc.subject | Optical Coherence Tomography Angiography | es_ES |
dc.subject | Vascularity | es_ES |
dc.title | Automatic extraction of vascularity measurements using OCT-A images | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Procedia Computer Science | es_ES |
UDC.volume | 126 | es_ES |
UDC.startPage | 273 | es_ES |
UDC.endPage | 281 | es_ES |
UDC.conferenceTitle | International Conference on Knowledge Based and Intelligent Information and Engineering Systems (KES2018) | es_ES |