COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images

The COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 has changed the world as we know it. An early diagnosis is crucial in order to prevent new outbreaks and control its rapid spread. Medical imaging techniques, such as X-ray or chest computed tomography, are commonly used for this purpose...

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Autores: Duran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080, Dominguez-Morales, J.P. (Juan Pedro)|||/items/3ca6db74-a92e-4104-8e81-7ca2044cea96, Corral-Jaime, J. (Jesús)|||/items/aba4503e-6970-43e0-9219-238766ac8852, Vicente-Diaz, S. (Saturnino)|||/items/b871769a-8901-4c60-9119-8c1a0e4dc279, Linares-Barranco, A. (Alejandro)|||/items/7e22feff-5a04-4201-a1f8-fc10a3634d13
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Navarra
Repositorio:Dadun. Depósito Académico Digital de la Universidad de Navarra
Idioma:inglés
OAI Identifier:oai:dadun.unav.edu:10171/65786
Acceso en línea:https://hdl.handle.net/10171/65786
Access Level:acceso abierto
Palabra clave:COVID-19
Deep learning
Convolutional neural networks
Medical image analysis
Computer-aided diagnosis
X-ray
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spelling COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray ImagesDuran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080Dominguez-Morales, J.P. (Juan Pedro)|||/items/3ca6db74-a92e-4104-8e81-7ca2044cea96Corral-Jaime, J. (Jesús)|||/items/aba4503e-6970-43e0-9219-238766ac8852Vicente-Diaz, S. (Saturnino)|||/items/b871769a-8901-4c60-9119-8c1a0e4dc279Linares-Barranco, A. (Alejandro)|||/items/7e22feff-5a04-4201-a1f8-fc10a3634d13COVID-19Deep learningConvolutional neural networksMedical image analysisComputer-aided diagnosisX-rayThe COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 has changed the world as we know it. An early diagnosis is crucial in order to prevent new outbreaks and control its rapid spread. Medical imaging techniques, such as X-ray or chest computed tomography, are commonly used for this purpose due to their reliability for COVID-19 diagnosis. Computer-aided diagnosis systems could play an essential role in aiding radiologists in the screening process. In this work, a novel Deep Learning-based system, called COVID-XNet, is presented for COVID-19 diagnosis in chest X-ray images. The proposed system performs a set of preprocessing algorithms to the input images for variability reduction and contrast enhancement, which are then fed to a custom Convolutional Neural Network in order to extract relevant features and perform the classification between COVID-19 and normal cases. The system is trained and validated using a 5-fold cross-validation scheme, achieving an average accuracy of 94.43% and an AUC of 0.988. The output of the system can be visualized using Class Activation Maps, highlighting the main findings for COVID-19 in X-ray images. These promising results indicate that COVID-XNet could be used as a tool to aid radiologists and contribute to the fight against COVID-19.Dadun. Depósito Académico Digital Universidad de Navarra20232023-03-2420202020-01-0120202020-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10171/65786reponame:Dadun. Depósito Académico Digital de la Universidad de Navarrainstname:Universidad de NavarraInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:dadun.unav.edu:10171/657862026-06-21T12:47:57Z
dc.title.none.fl_str_mv COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
title COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
spellingShingle COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
Duran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080
COVID-19
Deep learning
Convolutional neural networks
Medical image analysis
Computer-aided diagnosis
X-ray
title_short COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
title_full COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
title_fullStr COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
title_full_unstemmed COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
title_sort COVID-XNet: A Custom Deep Learning System to Diagnose and Locate COVID-19 in Chest X-ray Images
dc.creator.none.fl_str_mv Duran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080
Dominguez-Morales, J.P. (Juan Pedro)|||/items/3ca6db74-a92e-4104-8e81-7ca2044cea96
Corral-Jaime, J. (Jesús)|||/items/aba4503e-6970-43e0-9219-238766ac8852
Vicente-Diaz, S. (Saturnino)|||/items/b871769a-8901-4c60-9119-8c1a0e4dc279
Linares-Barranco, A. (Alejandro)|||/items/7e22feff-5a04-4201-a1f8-fc10a3634d13
author Duran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080
author_facet Duran-Lopez, L. (Lourdes)|||/items/26cf80f1-d115-4f78-8d17-1a892cbf4080
Dominguez-Morales, J.P. (Juan Pedro)|||/items/3ca6db74-a92e-4104-8e81-7ca2044cea96
Corral-Jaime, J. (Jesús)|||/items/aba4503e-6970-43e0-9219-238766ac8852
Vicente-Diaz, S. (Saturnino)|||/items/b871769a-8901-4c60-9119-8c1a0e4dc279
Linares-Barranco, A. (Alejandro)|||/items/7e22feff-5a04-4201-a1f8-fc10a3634d13
author_role author
author2 Dominguez-Morales, J.P. (Juan Pedro)|||/items/3ca6db74-a92e-4104-8e81-7ca2044cea96
Corral-Jaime, J. (Jesús)|||/items/aba4503e-6970-43e0-9219-238766ac8852
Vicente-Diaz, S. (Saturnino)|||/items/b871769a-8901-4c60-9119-8c1a0e4dc279
Linares-Barranco, A. (Alejandro)|||/items/7e22feff-5a04-4201-a1f8-fc10a3634d13
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Dadun. Depósito Académico Digital Universidad de Navarra
dc.subject.none.fl_str_mv COVID-19
Deep learning
Convolutional neural networks
Medical image analysis
Computer-aided diagnosis
X-ray
topic COVID-19
Deep learning
Convolutional neural networks
Medical image analysis
Computer-aided diagnosis
X-ray
description The COVID-19 pandemic caused by the new coronavirus SARS-CoV-2 has changed the world as we know it. An early diagnosis is crucial in order to prevent new outbreaks and control its rapid spread. Medical imaging techniques, such as X-ray or chest computed tomography, are commonly used for this purpose due to their reliability for COVID-19 diagnosis. Computer-aided diagnosis systems could play an essential role in aiding radiologists in the screening process. In this work, a novel Deep Learning-based system, called COVID-XNet, is presented for COVID-19 diagnosis in chest X-ray images. The proposed system performs a set of preprocessing algorithms to the input images for variability reduction and contrast enhancement, which are then fed to a custom Convolutional Neural Network in order to extract relevant features and perform the classification between COVID-19 and normal cases. The system is trained and validated using a 5-fold cross-validation scheme, achieving an average accuracy of 94.43% and an AUC of 0.988. The output of the system can be visualized using Class Activation Maps, highlighting the main findings for COVID-19 in X-ray images. These promising results indicate that COVID-XNet could be used as a tool to aid radiologists and contribute to the fight against COVID-19.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01
2020
2020-01-01
2023
2023-03-24
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10171/65786
url https://hdl.handle.net/10171/65786
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dadun. Depósito Académico Digital de la Universidad de Navarra
instname:Universidad de Navarra
instname_str Universidad de Navarra
reponame_str Dadun. Depósito Académico Digital de la Universidad de Navarra
collection Dadun. Depósito Académico Digital de la Universidad de Navarra
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