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Multi-task Convolutional Neural Networks for the End-to-end Simultaneous Segmentation and Screening of the Epiretinal Membrane in OCT Images
dc.contributor.author | Gende, M. | |
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Penedo, Manuel | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2024-05-03T11:53:13Z | |
dc.date.available | 2024-05-03T11:53:13Z | |
dc.date.issued | 2023-02-16 | |
dc.identifier.citation | M. Gende, J. D. Moura, J. Novo, M. F. González Penedo, y M. Ortega, «Multi-task Convolutional Neural Networks for the End-to-end Simultaneous Segmentation and Screening of the Epiretinal Membrane in OCT Images», In: Alvaro Leitao and Lucía Ramos (editors). Proceedings of V XoveTIC Conference. XoveTIC 2022, Kalpa Publications in Computing, vol 14, pp. 77-73. doi: 10.29007/xxh7. | es_ES |
dc.identifier.issn | 2515-1762 | |
dc.identifier.uri | http://hdl.handle.net/2183/36401 | |
dc.description | V Congreso XoveTIC, organizado por el Centro de Investigación en TIC da Universidade da Coruña (CITIC), 5 y 6 de octubre de 2022, A Coruña. | es_ES |
dc.description.abstract | [Absctract]: The Epiretinal Membrane (ERM) is an ocular pathology that causes visual distortion. In order to detect and treat the ERM, ophthalmologists visually inspect Optical Coherence Tomography (OCT) images.This is a costly and subjective process. In this work, we present three different fully automatic, end-to-end approaches that make use of multi-task learning to simultaneously screen for and segment ERM symptoms in OCT images. These approaches were implemented into three architectures that capitalise on the way the models share a single architecture for the two complementary tasks. | es_ES |
dc.description.sponsorship | This research was funded by Instituto de Salud Carlos III, Government of Spain, [DTS18/00136]; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, [RTI2018-095894-B-I00]; Ministerio de Ciencia e Innovación, Government of Spain through the research project [PID2019-108435RB-I00]; Consellería de Cultura, Educación e Universidade, Xunta de Galicia, Grupos de Referencia Competitiva, [ED431C 2020/24], predoctoral grant [ED481A 2021/161]; Axencia Galega de Innovación (GAIN), Xunta de Galicia, [IN845D 2020/38]; CITIC, Centro de Investigación de Galicia [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; ED481A 2021/161 | 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 | EasyChair | 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/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/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108435RB-I00/ES/CUANTIFICACIÓN Y CARACTERIZACIÓN COMPUTACIONAL DE IMAGEN MULTIMODAL OFTALMOLÓGICA: ESTUDIOS EN ESCLEROSIS MÚLTIPLE | es_ES |
dc.relation.uri | https://doi.org/10.29007/xxh7 | es_ES |
dc.subject | Deep learning | es_ES |
dc.subject | Epiretinal membrane | es_ES |
dc.subject | Multi-task learning | es_ES |
dc.subject | Optical Coherence Tomography | es_ES |
dc.title | Multi-task Convolutional Neural Networks for the End-to-end Simultaneous Segmentation and Screening of the Epiretinal Membrane in OCT Images | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Kalpa Publications in Computing | es_ES |
UDC.volume | 14 | es_ES |
UDC.startPage | 77 | es_ES |
UDC.endPage | 79 | es_ES |
UDC.conferenceTitle | Proceedings of V XoveTIC Conference. XoveTIC 2022 | es_ES |