Deep Learning on Chest X-ray Images to ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19
Auteur(s) :
Hammoudi, Karim [Auteur correspondant]
Institut de Recherche en Informatique Mathématiques Automatique Signal [IRIMAS]
Benhabiles, Halim [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Bio-Micro-Electro-Mechanical Systems - IEMN [BIOMEMS - IEMN]
JUNIA [JUNIA]
Melkemi, Mahmoud [Auteur]
Institut de Recherche en Informatique Mathématiques Automatique Signal [IRIMAS]
Université de Haute-Alsace (UHA) Mulhouse - Colmar [Université de Haute-Alsace (UHA)]
Dornaika, Fadi [Auteur]
Universidad del Pais Vasco / Euskal Herriko Unibertsitatea [Espagne] [UPV/EHU]
Ikerbasque - Basque Foundation for Science
Arganda-Carreras, Ignacio [Auteur]
University of the Basque Country = Euskal Herriko Unibertsitatea [UPV / EHU]
Ikerbasque - Basque Foundation for Science
Collard, Dominique [Auteur]
Laboratory for Integrated Micro Mechatronics Systems [LIMMS]
Scherpereel, Arnaud [Auteur]
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Institut de Recherche en Informatique Mathématiques Automatique Signal [IRIMAS]
Benhabiles, Halim [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Bio-Micro-Electro-Mechanical Systems - IEMN [BIOMEMS - IEMN]
JUNIA [JUNIA]
Melkemi, Mahmoud [Auteur]
Institut de Recherche en Informatique Mathématiques Automatique Signal [IRIMAS]
Université de Haute-Alsace (UHA) Mulhouse - Colmar [Université de Haute-Alsace (UHA)]
Dornaika, Fadi [Auteur]
Universidad del Pais Vasco / Euskal Herriko Unibertsitatea [Espagne] [UPV/EHU]
Ikerbasque - Basque Foundation for Science
Arganda-Carreras, Ignacio [Auteur]
University of the Basque Country = Euskal Herriko Unibertsitatea [UPV / EHU]
Ikerbasque - Basque Foundation for Science
Collard, Dominique [Auteur]
Laboratory for Integrated Micro Mechatronics Systems [LIMMS]
Scherpereel, Arnaud [Auteur]
Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI]
Titre de la revue :
Signal & Image Processing : An International Journal
Pagination :
75
Éditeur :
AIRCC Publishing Corporation
Date de publication :
2021-07
ISSN :
2229-3922
Mot(s)-clé(s) en anglais :
image detection
radiology
X-ray
COVID-19
pneumonia
radiology
X-ray
COVID-19
pneumonia
Discipline(s) HAL :
Informatique [cs]/Imagerie médicale
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Traitement des images [eess.IV]
Informatique [cs]/Bio-informatique [q-bio.QM]
Informatique [cs]/Biotechnologie
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Traitement des images [eess.IV]
Informatique [cs]/Bio-informatique [q-bio.QM]
Informatique [cs]/Biotechnologie
Résumé en anglais : [en]
Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus ...
Lire la suite >Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus pandemic. In many cases, this disease causes pneumonia. Since pulmonary infections can be observed through radiography images, this paper investigates deep learning methods for automatically analyzing query chest X-ray images with the hope to bring precision tools to health professionals towards screening the COVID-19 and diagnosing confirmed patients. In this context, training datasets, deep learning architectures and analysis strategies have been experimented from publicly open sets of chest X-ray images. Tailored deep learning models are proposed to detect pneumonia infection cases, notably viral cases. It is assumed that viral pneumonia cases detected during an epidemic COVID-19 context have a high probability to presume COVID-19 infections. Moreover, easy-to-apply health indicators are proposed for estimating infection status and predicting patient status from the detected pneumonia cases. Experimental results show possibilities of training deep learning models over publicly open sets of chest X-ray images towards screening viral pneumonia. Chest X-ray test images of COVID-19 infected patients are successfully diagnosed through detection models retained for their performances. The efficiency of proposed health indicators is highlighted through simulated scenarios of patients presenting infections and health problems by combining real and synthetic health data.Lire moins >
Lire la suite >Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus pandemic. In many cases, this disease causes pneumonia. Since pulmonary infections can be observed through radiography images, this paper investigates deep learning methods for automatically analyzing query chest X-ray images with the hope to bring precision tools to health professionals towards screening the COVID-19 and diagnosing confirmed patients. In this context, training datasets, deep learning architectures and analysis strategies have been experimented from publicly open sets of chest X-ray images. Tailored deep learning models are proposed to detect pneumonia infection cases, notably viral cases. It is assumed that viral pneumonia cases detected during an epidemic COVID-19 context have a high probability to presume COVID-19 infections. Moreover, easy-to-apply health indicators are proposed for estimating infection status and predicting patient status from the detected pneumonia cases. Experimental results show possibilities of training deep learning models over publicly open sets of chest X-ray images towards screening viral pneumonia. Chest X-ray test images of COVID-19 infected patients are successfully diagnosed through detection models retained for their performances. The efficiency of proposed health indicators is highlighted through simulated scenarios of patients presenting infections and health problems by combining real and synthetic health data.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Source :
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- https://hal.archives-ouvertes.fr/hal-02533605/document
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- https://hal.archives-ouvertes.fr/hal-02533605/document
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- https://link.springer.com/content/pdf/10.1007/s10916-021-01745-4.pdf
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- https://hal.archives-ouvertes.fr/hal-02533605/document
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- Pre-print_image_analysis_COVID-19_pneumonia_.pdf
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- s10916-021-01745-4.pdf
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