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Fully automated identification and clinical classification of macular edema using optical coherence tomography images
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Samagaio, Gabriela | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Fernández, María Isabel | |
dc.contributor.author | Gómez-Ulla, Francisco | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2024-06-20T09:14:42Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Moura, Joaquim de, Gabriela Samagaio, Jorge Novo, María Isabel Fernández, Francisco Gómez-Ulla, y Marcos Ortega. 2020. «Fully automated identification and clinical classification of macular edema using optical coherence tomography images». En Diabetes and Retinopathy, editado por Ayman S. El-Baz y Jasjit S. Suri, 45-67. Elsevier. https://doi.org/10.1016/B978-0-12-817438-8.00003-1. | es_ES |
dc.identifier.isbn | 978-0-12-817438-8 | |
dc.identifier.uri | http://hdl.handle.net/2183/37200 | |
dc.description.abstract | [Absctract]: Diabetic macular edema is a relevant ocular disease associated with diabetes mellitus that constitutes a concerning global health issue. This disease is one of the main causes of reversible blindness in industrialized countries, despite the availability of effective health interventions. This macular disorder is a consequence of the appearance of abnormal fluid regions within the main tissues of the retina that significantly decrease the patient's visual acuity. These fluid accumulations are also known as macular edemas (MEs). In this chapter, we present a computational methodology for the identification and clinical classification of ME using optical coherence tomography (OCT) scans, following the clinical classification of reference in the ophthalmological field. The presented system was tested with a dataset composed of 170 OCT scans retrieved from different patients that were labeled by a clinical expert. The presented system obtained satisfactory results in the localization of the area affected by each type of ME, even when they are combined in the same region of the retina. This fully automatic tool has demonstrated to be very useful not only for patients (helping in the early diagnosis of diseases that, consequently, improve their quality of life and well-being), but also in clinical systems by reducing costs. | 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 DTS15/00153 and DTS18/00136 research projects and by the Ministerio de Ciencia, Innovacio´n y Universidades, Government of Spain through the DPI2015-69948-R and RTI2018- 095894-B-I00 research projects. Also, this work has received financial support from the European Union (European Regional Development Fund [ERDF]) and the Xunta de Galicia, Centro singular de investigacio´n de Galicia accreditation 2016–19, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. 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/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/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 | 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/B978-0-12-817438-8.00003-1 | es_ES |
dc.rights | © 2020 Elsevier Inc. All rights reserved. | es_ES |
dc.subject | Optical coherence tomography | es_ES |
dc.subject | Macular edemas | es_ES |
dc.subject | Diabetic macular edema | es_ES |
dc.subject | Age-related macular degeneration | es_ES |
dc.subject | Serous retinal detachment | es_ES |
dc.subject | Diffuse retinal thickening | es_ES |
dc.title | Fully automated identification and clinical classification of macular edema using optical coherence tomography images | es_ES |
dc.type | info:eu-repo/semantics/bookPart | es_ES |
dc.rights.access | info:eu-repo/semantics/embargoedAccess | es_ES |
dc.date.embargoEndDate | 9999-99-99 | es_ES |
dc.date.embargoLift | 10007-06-07 | |
UDC.journalTitle | Diabetes and Retinopathy. Volume 2: Computer-Assisted Diagnosis | es_ES |
UDC.startPage | 45 | es_ES |
UDC.endPage | 67 | es_ES |