Computational Radiological Screening of Patients with COVID-19 Using Chest X-ray Images from Portable Devices

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UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvGrupo de Visión Artificial e Recoñecemento de Patróns (VARPA)es_ES
UDC.issue1es_ES
UDC.journalTitleEngineering Proceedingses_ES
UDC.startPage1es_ES
UDC.volume7es_ES
dc.contributor.authorMoura, Joaquim de
dc.contributor.authorRamos, Lucía
dc.contributor.authorVidal, Plácido
dc.contributor.authorCruz, Nilfa Milena
dc.contributor.authorAbelairas López, Laura
dc.contributor.authorCastro López, Eva
dc.contributor.authorNovo Buján, Jorge
dc.contributor.authorOrtega Hortas, Marcos
dc.date.accessioned2022-01-21T19:37:50Z
dc.date.available2022-01-21T19:37:50Z
dc.date.issued2021
dc.descriptionPresented at the 4th XoveTIC Conference, A Coruña, Spain, 7–8 October 2021.es_ES
dc.description.abstract[Abstract] This work presents a fully automatic system for the screening of chest X-ray images from portable devices under the analysis of three different clinical categories: normal, pathological cases of pulmonary diseases with findings similar to those of COVID-19, and COVID-19 cases. Our methodology was validated using a dataset retrieved specifically for this study, which was provided by the Radiology Service of the Complexo Hospitalario Universitario A Coruña (CHUAC). Despite the poor quality conditions of chest X-ray images acquired by portable devices, satisfactory results were obtained, demonstrating the robustness and great potential of the proposed system to help front-line clinicians in the diagnosis and treatment of patients with COVID-19.es_ES
dc.description.sponsorshipThis research was funded by Instituto de Salud Carlos III, Government of Spain, DTS18/00136 research project; Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project, as well as through Ayudas para la formación de profesorado universitario (FPU), Ref. FPU18/02271; 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 through the postdoctoral grant contract ref. ED481B 2021/059; and 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, received 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.sponsorshipXunta de Galicia; ED481B 2021/059es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2020/24es_ES
dc.description.sponsorshipXunta de Galicia; IN845D 2020/38es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.identifier.citationde Moura, J.; Ramos, L.; Vidal, P.L.; Cruz, M.; Abelairas, L.; Castro, E.; Novo, J.; Ortega, M. Computational Radiological Screening of Patients with COVID-19 Using Chest X-ray Images from Portable Devices. Eng. Proc. 2021, 7, 1. https://doi.org/10.3390/engproc2021007001es_ES
dc.identifier.doi10.3390/engproc2021007001
dc.identifier.urihttp://hdl.handle.net/2183/29462
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.urihttps://doi.org/10.3390/engproc2021007001es_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectComputer-aided diagnosises_ES
dc.subjectPortable chest X-ray imaginges_ES
dc.subjectCOVID-19es_ES
dc.subjectPneumoniaes_ES
dc.subjectDeep learninges_ES
dc.titleComputational Radiological Screening of Patients with COVID-19 Using Chest X-ray Images from Portable Deviceses_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication201e7998-8cd7-4e49-b19d-e60f2ec59c79
relation.isAuthorOfPublication0fcd917d-245f-4650-8352-eb072b394df0
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relation.isAuthorOfPublication.latestForDiscovery028dac6b-dd82-408f-bc69-0a52e2340a54

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