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dc.contributor.authorVidal, Plácido
dc.contributor.authorMoura, Joaquim de
dc.contributor.authorAlmuiña, Pablo
dc.contributor.authorFernández, María Isabel
dc.contributor.authorOrtega Hortas, Marcos
dc.contributor.authorNovo Buján, Jorge
dc.date.accessioned2024-06-05T16:38:13Z
dc.date.available2024-06-05T16:38:13Z
dc.date.issued2023-08
dc.identifier.citationVidal, P.L., de Moura, J., Almuiña, P. et al. Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images. Appl Intell 53, 25897–25918 (2023). https://doi.org/10.1007/s10489-023-04656-8es_ES
dc.identifier.issn0924-669X
dc.identifier.issn1573-7497
dc.identifier.urihttp://hdl.handle.net/2183/36813
dc.description.abstract[Abstract]: Optical Coherence Tomography Angiography or OCTA represents one of the main means of diagnosis of Age-related Macular Degeneration (AMD), the leading cause of blindness in developed countries. This eye disease is characterized by Macular Neovascularization (MNV), the formation of vessels that tear through the retinal tissues. Four types of MNV can be distinguished, each representing different levels of severity. Both the aggressiveness of the treatment and the recovery of the patient rely on an early detection and correct diagnosis of the stage of the disease. In this work, we propose the first fully-automatic grading methodology that considers all the four clinical types of MNV at the three most relevant OCTA scanning depths for the diagnosis of AMD. We perform both a comprehensive ablation study on the contribution of said depths and an analysis of the attention maps of the network in collaboration with experts of the domain. Our proposal aims to ease the diagnosis burden and decrease the influence of subjectivity on it, offering a explainable grading through the visualization of the attention of the expert models. Our grading proposal achieved satisfactory results with an AUC of 0.9224 ± 0.0381. Additionally, the qualitative analysis performed in collaboration with experts revealed the relevance of the avascular plexus in the grading of all three types of MNV (despite not being directly involved in some of them). Thus, our proposal is not only able to robustly detect MNV in complex scenarios, but also aided to discover previously unconsidered relationships between plexuses.es_ES
dc.description.sponsorshipFunding for open access charge: Universidade da Coruña/CISUG. This research was funded by Instituto de Salud Carlos III, Government of Spain, PI17/00940 research project; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project, Ayudas para la formación de profesorado universitario (FPU), grant ref. FPU18/02271 and Ayudas complementarias de movilidad destinadas a beneficiarios del programa de Formación del Profesorado Universitario (FPU) EST22/00696; Ministerio de Ciencia e Innovación, Government of Spain through the research project with reference PID2019-108435RB-I00; Consellería de Cultura, Educación e Universidade, Xunta de Galicia, Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovación (GAIN), Xunta de Galicia, grant ref. IN845D 2020/38;CITIC, Centro de Investigación de Galicia ref. ED431G 2019/01, receives financial support from Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia, through the ERDF (80%) and Secretaría Xeral de Universidades (20%). Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2020/24es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipFinanciado para publicación en acceso aberto: Universidade da Coruña/CISUGes_ES
dc.description.sponsorshipXunta de Galicia; IN845D 2020/38es_ES
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.relationinfo:eu-repo/grantAgreement/ISCIII/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013–2016/PI17%2F00940/ES/MEDICINA PERSONALIZADA EN LA DEGENERACION MACULAR ASOCIADA A LA EDAD EN BASE A TECNICAS DE IMAGEN, FARMACOCINETICA Y FARMACOGENETICA (IMAGEPKGEN-DMAE)es_ES
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 OFTALMOLOGICAes_ES
dc.relationinfo:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU18%2F02271/ES/es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108435RB-I00/ES/CUANTIFICACION Y CARACTERIZACION COMPUTACIONAL DE IMAGEN MULTIMODAL OFTALMOLOGICA: ESTUDIOS EN ESCLEROSIS MULTIPLEes_ES
dc.relationinfo:eu-repo/grantAgreement//Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/EST22%2F00696/ES/es_ES
dc.relation.urihttps://doi.org/10.1007/s10489-023-04656-8es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectOptical coherence tomography angiographyes_ES
dc.subjectComputer-aided diagnosises_ES
dc.subjectAge-related macular degenerationes_ES
dc.subjectMulti-depth analysises_ES
dc.subjectQualitative analysises_ES
dc.subjectAttention mapses_ES
dc.titleComprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA imageses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleApplied Intelligencees_ES
UDC.volume53es_ES
UDC.startPage25897es_ES
UDC.endPage25918es_ES
dc.identifier.doi10.1007/s10489-023-04656-8


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