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dc.contributor.authorCabaleiro, Pablo
dc.contributor.authorMoura, Joaquim de
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorCharlón, Pablo
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2019-11-28T16:29:17Z
dc.date.available2019-11-28T16:29:17Z
dc.date.issued2019-11-21
dc.identifier.citationCabaleiro, P.; de Moura, J.; Novo, J.; Charlón, P.; Ortega, M. Automatic Identification and Representation of the Cornea–Contact Lens Relationship Using AS-OCT Images. Sensors 2019, 19, 5087. https://doi.org/10.3390/s19235087es_ES
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/2183/24404
dc.description.abstract[Abstract] The clinical study of the cornea–contact lens relationship is widely used in the process of adaptation of the scleral contact lens (SCL) to the ocular morphology of patients. In that sense, the measurement of the adjustment between the SCL and the cornea can be used to study the comfort or potential damage that the lens may produce in the eye. The current analysis procedure implies the manual inspection of optical coherence tomography of the anterior segment images (AS-OCT) by the clinical experts. This process presents several limitations such as the inability to obtain complex metrics, the inaccuracies of the manual measurements or the requirement of a time-consuming process by the expert in a tedious process, among others. This work proposes a fully-automatic methodology for the extraction of the areas of interest in the study of the cornea–contact lens relationship and the measurement of representative metrics that allow the clinicians to measure quantitatively the adjustment between the lens and the eye. In particular, three distance metrics are herein proposed: Vertical, normal to the tangent of the region of interest and by the nearest point. Moreover, the images are classified to characterize the analysis as belonging to the central cornea, peripheral cornea, limbus or sclera (regions where the inner layer of the lens has already joined the cornea). Finally, the methodology graphically presents the results of the identified segmentations using an intuitive visualization that facilitates the analysis and diagnosis of the patients by the clinical experts.es_ES
dc.description.sponsorshipThis work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research projects and by the Ministerio de Ciencia, Innovación y Universidades, Government of Spain through the DPI2015-69948-R and RTI2018-095894-B-I00 research projects. Moreover, this work has received financial support from the European Union (European Regional Development Fund—ERDF) and the Xunta de Galicia, Grupos de Referencia Competitiva, Ref. ED431C 2016-047.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2016-047.es_ES
dc.language.isoenges_ES
dc.publisherMDPI AGes_ES
dc.relationinfo:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/DTS18%2F00136/ES/Plataforma online para prevención y detección precoz de enfermedad vascular mediante análisis automatizado de información e imagen clínica
dc.relationinfo: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
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095894-B-I00/ES/DESARROLLO DE TECNOLOGIAS INTELIGENTES PARA DIAGNOSTICO DE LA DMAE BASADAS EN EL ANALISIS AUTOMATICO DE NUEVAS MODALIDADES HETEROGENEAS DE ADQUISICION DE IMAGEN OFTALMOLOGICA
dc.relation.urihttps://doi.org/10.3390/s19235087es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)es_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectComputer-aided diagnosises_ES
dc.subjectOptical coherence tomographyes_ES
dc.subjectAnterior segmentes_ES
dc.subjectCorneaes_ES
dc.subjectContact lenses_ES
dc.titleAutomatic Identification and Representation of the Cornea–Contact Lens Relationship Using AS-OCT Imageses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleSensorses_ES
UDC.volume19es_ES
UDC.issue23es_ES
UDC.startPage5087es_ES
dc.identifier.doi10.3390/s19235087


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