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Automated segmentation of the central serous chorioretinopathy fluid regions using optical coherence tomography scans
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.contributor.author | Barreira, Noelia | |
dc.contributor.author | Charlón, Pablo | |
dc.date.accessioned | 2024-06-07T10:40:36Z | |
dc.date.available | 2024-06-07T10:40:36Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | J. de Moura, J. Novo, M. Ortega, N. Barreira and M. G. Penedo, "Automated Segmentation of the Central Serous Chorioretinopathy fluid regions using Optical Coherence Tomography Scans," 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 2021, pp. 1-6, doi: 10.1109/CBMS52027.2021.00008. | es_ES |
dc.identifier.isbn | 978-166544121-6 | |
dc.identifier.issn | 1063-7125 | |
dc.identifier.uri | http://hdl.handle.net/2183/36836 | |
dc.description | 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), Aveiro, Portugal, 2021 | es_ES |
dc.description | 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/CBMS52027.2021.00008 | es_ES |
dc.description.abstract | [Abstract]: Central serous chorioretinopathy is one of the most frequent causes of vision impairment among middle-aged adults. Optical Coherence Tomography (OCT) is a non-invasive diagnostic technique that is commonly used for the monitoring of this relevant eye disease. In this context, this paper proposes a fully automatic system for the characterization of intraretinal pathological fluid regions associated with central serous chori-oretinopathy using OCT scans. To achieve this, we adapted an end-to-end fully convolutional architecture for semantic pixel-wise segmentation. The proposed methodology was tested using a heterogeneous set of 100 OCT scans of different patients. Satisfactory results were obtained, reaching values of 0.9954pm 0.0007, 0.8792 \pm 0.0079 and 0.9651 \pm 0.0041 for the mean Accuracy, mean Jaccard index and mean Dice coefficient, respectively. The proposed system also demonstrated its competitive performance with respect to other state-of-the-art approaches. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2020/24 | |
dc.description.sponsorship | Xunta de Galicia; IN845D 2020/38 | |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | |
dc.description.sponsorship | This research was funded by Instituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia e Innovacion´ y Universidades, Government of Spain, RTI2018-095894-B-I00 research project; Ministerio de Ciencia e Innovacion, Government of Spain through ´ the research project with reference PID2019-108435RB-I00; Conseller´ıa de Cultura, Educacion e Universidade, Xunta de Galicia, Grupos de Referencia ´ Competitiva, grant ref. ED431C 2020/24; Axencia Galega de Innovacion´ (GAIN), Xunta de Galicia, grant ref. IN845D 2020/38; CITIC, Centro de Investigacion de Galicia ref. ED431G 2019/01, receives financial support from ´ Consellería de Educacion, Universidade e Formación Profesional, Xunta de ´ Galicia, through the ERDF (80%) and Secretaría Xeral de Universidades (20%). | |
dc.language.iso | eng | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | es_ES |
dc.relation | info:eu-repo/grantAgreement/ISCIII /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 | |
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 | |
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 | |
dc.relation.uri | https://doi.org/10.1109/CBMS52027.2021.00008 | es_ES |
dc.rights | © 2021 IEEE | es_ES |
dc.subject | central serous chorioretinopathy | es_ES |
dc.subject | Computer-aided diagnosis | es_ES |
dc.subject | optical coherence tomography | es_ES |
dc.subject | retinal imaging | es_ES |
dc.subject | segmentation | es_ES |
dc.title | Automated segmentation of the central serous chorioretinopathy fluid regions using optical coherence tomography scans | 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 |
dc.identifier.doi | 10.1109/CBMS52027.2021.00008 | |
UDC.conferenceTitle | IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS) | es_ES |