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A review of deep learning-based detection methods for COVID-19

COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the spread of infection. Lung images are used in the detection of coronavirus infection. Chest X-ray (CXR) and computed tomography (CT) images are available for the detection of COVID-19. Deep learning methods have be...

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Detalles Bibliográficos
Autores principales: Subramanian, Nandhini, Elharrouss, Omar, Al-Maadeed, Somaya, Chowdhury, Muhammed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Qatar University. Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8798789/
https://www.ncbi.nlm.nih.gov/pubmed/35180499
http://dx.doi.org/10.1016/j.compbiomed.2022.105233
Descripción
Sumario:COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the spread of infection. Lung images are used in the detection of coronavirus infection. Chest X-ray (CXR) and computed tomography (CT) images are available for the detection of COVID-19. Deep learning methods have been proven efficient and better performing in many computer vision and medical imaging applications. In the rise of the COVID pandemic, researchers are using deep learning methods to detect coronavirus infection in lung images. In this paper, the currently available deep learning methods that are used to detect coronavirus infection in lung images are surveyed. The available methodologies, public datasets, datasets that are used by each method and evaluation metrics are summarized in this paper to help future researchers. The evaluation metrics that are used by the methods are comprehensively compared.