Deep learning for COVID-19 detection based on CT images

Abstract COVID-19 has tremendously impacted patients and medical systems globally. Computed tomography images can effectively complement the reverse transcription-polymerase chain reaction testing. This study adopted a convolutional neural network for COVID-19 testing. We examined the performance of...

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Autores principales:	Wentao Zhao, Wei Jiang, Xinguo Qiu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c3add19cf23746b086c31d653063cc3e
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id	oai:doaj.org-article:c3add19cf23746b086c31d653063cc3e
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spelling	oai:doaj.org-article:c3add19cf23746b086c31d653063cc3e2021-12-02T16:14:02ZDeep learning for COVID-19 detection based on CT images10.1038/s41598-021-93832-22045-2322https://doaj.org/article/c3add19cf23746b086c31d653063cc3e2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93832-2https://doaj.org/toc/2045-2322Abstract COVID-19 has tremendously impacted patients and medical systems globally. Computed tomography images can effectively complement the reverse transcription-polymerase chain reaction testing. This study adopted a convolutional neural network for COVID-19 testing. We examined the performance of different pre-trained models on CT testing and identified that larger, out-of-field datasets boost the testing power of the models. This suggests that a priori knowledge of the models from out-of-field training is also applicable to CT images. The proposed transfer learning approach proves to be more successful than the current approaches described in literature. We believe that our approach has achieved the state-of-the-art performance in identification thus far. Based on experiments with randomly sampled training datasets, the results reveal a satisfactory performance by our model. We investigated the relevant visual characteristics of the CT images used by the model; these may assist clinical doctors in manual screening.Wentao ZhaoWei JiangXinguo QiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Wentao Zhao Wei Jiang Xinguo Qiu Deep learning for COVID-19 detection based on CT images
description	Abstract COVID-19 has tremendously impacted patients and medical systems globally. Computed tomography images can effectively complement the reverse transcription-polymerase chain reaction testing. This study adopted a convolutional neural network for COVID-19 testing. We examined the performance of different pre-trained models on CT testing and identified that larger, out-of-field datasets boost the testing power of the models. This suggests that a priori knowledge of the models from out-of-field training is also applicable to CT images. The proposed transfer learning approach proves to be more successful than the current approaches described in literature. We believe that our approach has achieved the state-of-the-art performance in identification thus far. Based on experiments with randomly sampled training datasets, the results reveal a satisfactory performance by our model. We investigated the relevant visual characteristics of the CT images used by the model; these may assist clinical doctors in manual screening.
format	article
author	Wentao Zhao Wei Jiang Xinguo Qiu
author_facet	Wentao Zhao Wei Jiang Xinguo Qiu
author_sort	Wentao Zhao
title	Deep learning for COVID-19 detection based on CT images
title_short	Deep learning for COVID-19 detection based on CT images
title_full	Deep learning for COVID-19 detection based on CT images
title_fullStr	Deep learning for COVID-19 detection based on CT images
title_full_unstemmed	Deep learning for COVID-19 detection based on CT images
title_sort	deep learning for covid-19 detection based on ct images
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c3add19cf23746b086c31d653063cc3e
work_keys_str_mv	AT wentaozhao deeplearningforcovid19detectionbasedonctimages AT weijiang deeplearningforcovid19detectionbasedonctimages AT xinguoqiu deeplearningforcovid19detectionbasedonctimages
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Deep learning for COVID-19 detection based on CT images

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