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Intraretinal fluid identification via enhanced maps using optical coherence tomography images
dc.contributor.author | Vidal, Plácido | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Penedo, Manuel | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2024-06-06T17:00:55Z | |
dc.date.available | 2024-06-06T17:00:55Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Plácido L. Vidal, Joaquim de Moura, Jorge Novo, Manuel G. Penedo, and Marcos Ortega, "Intraretinal fluid identification via enhanced maps using optical coherence tomography images," Biomed. Opt. Express 9, 4730-4754 (2018). https://doi.org/10.1364/BOE.9.004730 | es_ES |
dc.identifier.issn | 2156-7085 | |
dc.identifier.uri | http://hdl.handle.net/2183/36833 | |
dc.description.abstract | [Abstract]: Nowadays, among the main causes of blindness in developed countries are age-related macular degeneration (AMD) and the diabetic macular edema (DME). Both diseases present, as a common symptom, the appearance of cystoid fluid regions inside the retinal layers. Optical coherence tomography (OCT) image modality was one of the main medical imaging techniques for the early diagnosis and monitoring of AMD and DME via this intraretinal fluid detection and characterization. We present a novel methodology to identify these fluid accumulations by means of generating binary maps (offering a direct representation of these areas) and heat maps (containing the region confidence). To achieve this, a set of 312 intensity and texture-based features were studied. The most relevant features were selected using the sequential forward selection (SFS) strategy and tested with three archetypal classifiers: LDC, SVM and Parzen window. Finally, the most proficient classifier is used to create the proposed maps. All of the tested classifiers returned satisfactory results, the best classifier achieving a mean test accuracy higher than 94% in all of the experiments. The suitability of the maps was evaluated in a context of a screening issue with three different datasets obtained with two different devices, testing the capabilities of the system to work independently of the used OCT device. The experiments with the map creation were performed using 323 OCT images. Using only the binary maps, more than 91.33% of the images were correctly classified. With only the heat maps, the proposed methodology correctly separated 93.50% of the images. | es_ES |
dc.description.sponsorship | Instituto de Salud Carlos III (ISCIII) (PI14/02161, DTS15/00153); Ministerio de Economía, Industria y Competitividad, Gobierno de España (DPI2015-69948-R); Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia (ED431C 2016-047, ED431G/01). The authors take this opportunity to gratefully acknowledge the assistance and contributions of the opthalmologic services from the Complejo Hospitalario Universitario de Santiago (CHUS) and the Complejo Hospitalario Universitario de Ferrol (CHUF). | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2016-047 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Optica Publishing Group | 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/10.1364/BOE.9.004730 | es_ES |
dc.rights | © 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement | es_ES |
dc.subject | Optical Coherence Tomography | es_ES |
dc.subject | Intraretinal fluid detection | es_ES |
dc.subject | Age-related macular degeneration | es_ES |
dc.subject | Diabetic macular edema | es_ES |
dc.title | Intraretinal fluid identification via enhanced maps using optical coherence tomography images | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Biomedical Optics Express | es_ES |
UDC.volume | 9 | es_ES |
UDC.issue | 10 | es_ES |
UDC.startPage | 4730 | es_ES |
UDC.endPage | 4754 | es_ES |
dc.identifier.doi | 10.1364/BOE.9.004730 |
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