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Retinal Vascular Analysis in a Fully Automated Method for the Segmentation of DRT Edemas Using OCT Images
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Charlón, Pablo | |
dc.contributor.author | Fernández, María Isabel | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2020-01-14T16:36:02Z | |
dc.date.available | 2020-01-14T16:36:02Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | De Moura, Joaquim, et al. Retinal vascular analysis in a fully automated method for the segmentation of DRT edemas using OCT images. Procedia Computer Science, 2019, vol. 159, p. 600-609. | es_ES |
dc.identifier.issn | 1877-0509 | |
dc.identifier.uri | http://hdl.handle.net/2183/24631 | |
dc.description.abstract | [Abstract] Optical Coherence Tomography (OCT) is a well-established medical imaging technique that allows a complete analysis and evaluation of the main retinal structures and their histopathology properties. Diabetic Macular Edema (DME) implies the accumulation of intraretinal fluid within the macular region. Diffuse Retinal Thickening (DRT) edemas are considered a relevant case of DME disease, where the pathological regions are characterized by a “sponge-like” appearance and a reduced intraretinal reflectivity, being visible in OCT images. Additionally, the presence of other structures may alter the OCT image characteristics, confusing the pathological identification process. This is the case of the retinal vessels over all the eye fundus, whose presence produce shadow projections over the retinal layers that may hide the “sponge-like” appearance of the DRT edemas. Thus, in this paper, we present a proposal for the automatic extraction of DRT edemas, also using as reference the information provided by the automatic identifications of the retinal vessels in the OCT images. To do that, firstly, the system delimits three retinal regions of interest. These retinal regions facilitate the posterior identification of the vessel structures and the segmentation of the DRT regions. For the identification of the vessels structures, the method combined the localization of the upper bright vascular profiles with the presence of their corresponding lower dark vascular shadows. Finally, a learning strategy is implemented for the segmentation of the DRT edemas. Satisfactory results were obtained, reaching values of 0.8346 and 0.9051 of Jaccard index and Dice coefficient, respectively, for the extraction of the existing DRT edemas. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2016-047 | 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 DTS18/00136 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. | |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier BV | es_ES |
dc.relation | info: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.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 | |
dc.relation.uri | https://doi.org/10.1016/j.procs.2019.09.215 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | es_ES |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Computer-aided diagnosis | es_ES |
dc.subject | Optical Coherence Tomography | es_ES |
dc.subject | Diabetic macular edema | es_ES |
dc.subject | Retinal vascular structure | es_ES |
dc.title | Retinal Vascular Analysis in a Fully Automated Method for the Segmentation of DRT Edemas Using OCT Images | 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 | 159 | es_ES |
UDC.startPage | 600 | es_ES |
UDC.endPage | 609 | es_ES |
dc.identifier.doi | 10.1016/j.procs.2019.09.215 | |
UDC.conferenceTitle | 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems | es_ES |