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Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks
dc.contributor.author | Moura, Joaquim de | |
dc.contributor.author | Ramos, Lucía | |
dc.contributor.author | Vidal, Plácido | |
dc.contributor.author | Novo Buján, Jorge | |
dc.contributor.author | Ortega Hortas, Marcos | |
dc.date.accessioned | 2020-10-27T18:09:14Z | |
dc.date.available | 2020-10-27T18:09:14Z | |
dc.date.issued | 2020-08-21 | |
dc.identifier.citation | Moura, J.d.; Ramos, L.; Vidal, P.L.; Novo, J.; Ortega, M. Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks. Proceedings 2020, 54, 31. https://doi.org/10.3390/proceedings2020054031 | es_ES |
dc.identifier.issn | 2504-3900 | |
dc.identifier.uri | http://hdl.handle.net/2183/26558 | |
dc.description.abstract | [Abstract] The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization. In this context, chest X-ray imaging has become a remarkably powerful tool for the identification of patients with COVID-19 infections at an early stage when clinical symptoms may be unspecific or sparse. In this work, we propose a complete analysis of separability of COVID-19 and pneumonia in chest X-ray images by means of Convolutional Neural Networks. Satisfactory results were obtained that demonstrated the suitability of the proposed system, improving the efficiency of the medical screening process in the healthcare systems. | es_ES |
dc.description.sponsorship | This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research projects and by the Ministerio de Ciencia, Innovación y Universidades, Government of Spain through the RTI2018-095894-B-I00 research projects, as well as through Ayudas para la formación de profesorado universitario (FPU), Ref. FPU18/02271. Also, this work has received financial support from the European Union (European Regional Development Fund—ERDF) and the Xunta de Galicia, Centro de Investigación del Sistema Universitario de Galicia, Ref. ED431G 2019/01. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI AG | 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 | |
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/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/FPU18%2F02271/ES/ | |
dc.relation.uri | https://doi.org/10.3390/proceedings2020054031 | es_ES |
dc.rights | Atribución 4.0 Internacional | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Computer-aided diagnosis | es_ES |
dc.subject | Chest X-ray imaging | es_ES |
dc.subject | COVID-19 | es_ES |
dc.subject | Pneumonia | es_ES |
dc.subject | Deep learning | es_ES |
dc.title | Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Proceedings | es_ES |
UDC.volume | 54 | es_ES |
UDC.issue | 1 | es_ES |
UDC.startPage | 31 | es_ES |
dc.identifier.doi | 10.3390/proceedings2020054031 | |
UDC.conferenceTitle | 3rd XoveTIC Conference; A Coruña, Spain; 8–9 October 2020 | es_ES |
UDC.coleccion | Investigación | |
UDC.departamento | Ciencias da Computación e Tecnoloxías da Información | |
UDC.grupoInv | Grupo de Visión Artificial e Recoñecemento de Patróns (VARPA) |
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