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Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images
dc.contributor.author | Vidal, Plácido | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.contributor.author | Cardoso, Jaime S. | |
dc.date.accessioned | 2024-06-13T17:03:59Z | |
dc.date.available | 2024-06-13T17:03:59Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | P. L. Vidal, J. de Moura, J. Novo, M. Ortega and J. S. Cardoso, "Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10095039. | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/36908 | |
dc.description | © 2023 IEEE. This version of the paper has been accepted for publication. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published paper is available online at: https://doi.org/10.1109/ICASSP49357.2023.10095039 | es_ES |
dc.description | Presentado en: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 04-10 June 2023 | es_ES |
dc.description.abstract | [Abstract]: Optical Coherence Tomography (OCT) is the major diagnostic tool for the leading cause of blindness in developed countries: Diabetic Macular Edema (DME). Depending on the type of fluid accumulations, different treatments are needed. In particular, Cystoid Macular Edemas (CMEs) represent the most severe scenario, while Diffuse Retinal Thickening (DRT) is an early indicator of the disease but a challenging scenario to detect. While methodologies exist, their explanatory power is limited to the input sample itself. However, due to the complexity of these accumulations, this may not be enough for a clinician to assess the validity of the classification. Thus, in this work, we propose a novel approach based on multi-prototype networks with vision transformers to obtain an example-based explainable classification. Our proposal achieved robust results in two representative OCT devices, with a mean accuracy of 0.9099 ± 0.0083 and 0.8582 ± 0.0126 for CME and DRT-type fluid accumulations, respectively. | es_ES |
dc.description.sponsorship | 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%). | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2020/24 | es_ES |
dc.description.sponsorship | Xunta de Galicia; IN845D 2020/38 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation | info: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.relation | info: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 | es_ES |
dc.relation | info:eu-repo/grantAgreement/MECD/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/FPU18%2F02271/ES/ | es_ES |
dc.relation | info:eu-repo/grantAgreement//Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/EST22%2F00696/ES/ | es_ES |
dc.relation | info: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 MULTIPLE | es_ES |
dc.relation.uri | https://doi.org/10.1109/ICASSP49357.2023.10095039 | es_ES |
dc.rights | © 2023 IEEE | es_ES |
dc.subject | Multi-Prototype | es_ES |
dc.subject | Transformers | es_ES |
dc.subject | Optical Coherence Tomography | es_ES |
dc.subject | Diabetic Macular Edema | es_ES |
dc.subject | Explainable Artificial Intelligence | es_ES |
dc.title | Transformer-Based Multi-Prototype Approach for Diabetic Macular Edema Analysis in OCT Images | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.startPage | 1 | es_ES |
UDC.endPage | 5 | es_ES |
dc.identifier.doi | 10.1109/ICASSP49357.2023.10095039 | |
UDC.conferenceTitle | ICASSP 2023 | es_ES |