Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection
Abstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-95680-6 |
| _version_ | 1819200344021794816 |
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| author | Jie Hou Terry Gao |
| author_facet | Jie Hou Terry Gao |
| author_sort | Jie Hou |
| collection | DOAJ |
| description | Abstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The explainable method is also used in the DCNN to select instances of the X-ray dataset images to explain the behavior of training-learning models to achieve higher prediction accuracy. The average accuracy of our method is above 96%, which can replace manual reading and has the potential to be applied to large-scale rapid screening of COVID-9 for widely use cases. |
| first_indexed | 2024-12-23T03:30:44Z |
| format | Article |
| id | doaj.art-545602688df14dda9eb1eb3571c562bd |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-23T03:30:44Z |
| publishDate | 2021-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-545602688df14dda9eb1eb3571c562bd2022-12-21T18:01:41ZengNature PortfolioScientific Reports2045-23222021-08-0111111510.1038/s41598-021-95680-6Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detectionJie Hou0Terry Gao1School of Biomedical Engineering, Guangdong Medical UniversityCounties Manukau District Health BoardAbstract To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a new diagnosis platform using a deep convolutional neural network (DCNN) that is able to assist radiologists with diagnosis by distinguishing COVID-19 pneumonia from non-COVID-19 pneumonia in patients based on chest X-ray classification and analysis. Such a tool can save time in interpreting chest X-rays and increase the accuracy and thereby enhance our medical capacity for the detection and diagnosis of COVID-19. The explainable method is also used in the DCNN to select instances of the X-ray dataset images to explain the behavior of training-learning models to achieve higher prediction accuracy. The average accuracy of our method is above 96%, which can replace manual reading and has the potential to be applied to large-scale rapid screening of COVID-9 for widely use cases.https://doi.org/10.1038/s41598-021-95680-6 |
| spellingShingle | Jie Hou Terry Gao Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection Scientific Reports |
| title | Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection |
| title_full | Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection |
| title_fullStr | Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection |
| title_full_unstemmed | Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection |
| title_short | Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection |
| title_sort | explainable dcnn based chest x ray image analysis and classification for covid 19 pneumonia detection |
| url | https://doi.org/10.1038/s41598-021-95680-6 |
| work_keys_str_mv | AT jiehou explainabledcnnbasedchestxrayimageanalysisandclassificationforcovid19pneumoniadetection AT terrygao explainabledcnnbasedchestxrayimageanalysisandclassificationforcovid19pneumoniadetection |