Deep Learning Models for Justified Referral in AI Glaucoma Screening

UDC.coleccionInvestigación
UDC.conferenceTitleISBI 2024
UDC.departamentoCiencias da Computación e Tecnoloxías da Información
UDC.grupoInvGrupo de Visión Artificial e Recoñecemento de Patróns (VARPA)
UDC.institutoCentroINIBIC - Instituto de Investigacións Biomédicas de A Coruña
dc.contributor.authorCasado-García, Ángela
dc.contributor.authorHeras, Jónathan
dc.contributor.authorOrtega Hortas, Marcos
dc.contributor.authorRamos, Lucía
dc.date.accessioned2026-02-18T08:43:29Z
dc.date.available2026-02-18T08:43:29Z
dc.date.issued2024
dc.descriptionPresented at: 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 27-30 May 2024, Athens, Greece This version of the article has been accepted for publication, after peer review. 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 Version of Record is available online at: https://doi.org/10.1109/ISBI56570.2024.10635680
dc.description.abstract[Abstract]: Glaucoma is an optic disease that leads to blindness, but this might be avoided with an early diagnosis thanks to a screening test. The JustRAIGS Challenge was organised to develop solutions for glaucoma screening from retinal fundus images that not only classify fundus images as "referrable"or "no referable"but also identify specific characteristics or abnormalities that may be present in the fundus images of glaucoma patients. In this work, we present our solution to this challenge based on the study of several combinations of fundus images and their associated optic disc and cup. For the binary task, our solution consists of the ensemble of a ConvNext model and a Swin model that achieves a sensitivity at 95% specificity of 0.8570; whereas, for the multi-label task, our ConvNext model achieved a Hamming Loss of 0.1930.
dc.description.sponsorshipThis work was partially supported by Grant PID2020-115225RBI00 funded by MCIN/AEI/10.13039/501100011033, and by Ministerio de Ciencia e Innovación, Government of Spain through the research project with grant number PID2019-108435RB-I00. Ángela Casado-García has a FPI grant from Community of La Rioja 2020, at the moment, she is in the Postdoctoral Orientation Period (POP).
dc.identifier.citationÁ. Casado-García, J. Heras, M. Ortega and L. Ramos, "Deep Learning Models for Justified Referral in AI Glaucoma Screening," 2024 IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024, pp. 1-3, doi: 10.1109/ISBI56570.2024.10635680.
dc.identifier.doi10.1109/ISBI56570.2024.10635680
dc.identifier.isbn9798350313338
dc.identifier.issn1945-8452
dc.identifier.issn1945-7928
dc.identifier.urihttps://hdl.handle.net/2183/47438
dc.language.isoeng
dc.publisherIEEE
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-115225RB-I00/ES/ASPECTOS MATEMATICOS DEL PROCESAMIENTO DE IMAGENES BIOMEDICAS: METODOS TOPOLOGICOS Y DE CIENCIA DE DATOS
dc.relation.projectIDinfo: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/
dc.relation.urihttps://doi.org/10.1109/ISBI56570.2024.10635680
dc.rights© 2024 IEEE.
dc.rights.accessRightsopen access
dc.subjectGlaucoma
dc.subjectImage Classification
dc.subjectJustRAIGS
dc.subjectMulti-label classification
dc.titleDeep Learning Models for Justified Referral in AI Glaucoma Screening
dc.typeconference output
dspace.entity.typePublication
relation.isAuthorOfPublication1fb98665-ea68-4cd3-a6af-83e6bb453581
relation.isAuthorOfPublication201e7998-8cd7-4e49-b19d-e60f2ec59c79
relation.isAuthorOfPublication.latestForDiscovery1fb98665-ea68-4cd3-a6af-83e6bb453581

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Ortega_Marcos_2024_Deep_Learning_Models_for_Justified_Referral_in_AI_Glaucoma_Screening.pdf
Size:
370.27 KB
Format:
Adobe Portable Document Format