Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks
The novel coronavirus-2019 (Covid-19), a contagious disease became a pandemic and has caused overwhelming effects on the human lives and world economy. The detection of the contagious disease is vital to avert further spread and to promptly treat the infected people. The need of automated scientific...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Universidad Internacional de La Rioja (UNIR)
2021-05-01
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| Series: | International Journal of Interactive Multimedia and Artificial Intelligence |
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| Online Access: | https://www.ijimai.org/journal/bibcite/reference/2928 |
| _version_ | 1819204173306003456 |
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| author | Muhammad Irfan Khattak Mu’ath Al-Hasan Atif Jan Nasir Saleem Elena Verdú Numan Khurshid |
| author_facet | Muhammad Irfan Khattak Mu’ath Al-Hasan Atif Jan Nasir Saleem Elena Verdú Numan Khurshid |
| author_sort | Muhammad Irfan Khattak |
| collection | DOAJ |
| description | The novel coronavirus-2019 (Covid-19), a contagious disease became a pandemic and has caused overwhelming effects on the human lives and world economy. The detection of the contagious disease is vital to avert further spread and to promptly treat the infected people. The need of automated scientific assisting diagnostic methods to identify Covid-19 in the infected people has increased since less accurate automated diagnostic methods are available. Recent studies based on the radiology imaging suggested that the imaging patterns on X-ray images and Computed Tomography (CT) scans contain leading information about Covid-19 and is considered as a potential automated diagnosis method. Machine learning and deep learning techniques combined with radiology imaging can be helpful for accurate detection of the disease. A deep learning approach based on the multilayer-Spatial Convolutional Neural Network for automatic detection of Covid-19 using chest X-ray images and CT scans is proposed in this paper. The proposed model, named as the Multilayer Spatial Covid Convolutional Neural Network (MSCovCNN), provides an automated accurate diagnostics for Covid-19 detection. The proposed model showed 93.63% detection accuracy and 97.88% AUC (Area Under Curve) for chest x-ray images and 91.44% detection accuracy and 95.92% AUC for chest CT scans, respectively. We have used 5-tiered 2D-CNN frameworks followed by the Artificial Neural Network (ANN) and softmax classifier. In the CNN each convolution layer is followed by an activation function and a Maxpooling layer. The proposed model can be used to assist the radiologists in detecting the Covid-19 and confirming their initial screening. |
| first_indexed | 2024-12-23T04:31:36Z |
| format | Article |
| id | doaj.art-8dfde85a5e814929b437bb19fe414124 |
| institution | Directory Open Access Journal |
| issn | 1989-1660 1989-1660 |
| language | English |
| last_indexed | 2024-12-23T04:31:36Z |
| publishDate | 2021-05-01 |
| publisher | Universidad Internacional de La Rioja (UNIR) |
| record_format | Article |
| series | International Journal of Interactive Multimedia and Artificial Intelligence |
| spelling | doaj.art-8dfde85a5e814929b437bb19fe4141242022-12-21T18:00:01ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602021-05-0166152410.9781/ijimai.2021.04.002ijimai.2021.04.002Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural NetworksMuhammad Irfan KhattakMu’ath Al-HasanAtif JanNasir SaleemElena VerdúNuman KhurshidThe novel coronavirus-2019 (Covid-19), a contagious disease became a pandemic and has caused overwhelming effects on the human lives and world economy. The detection of the contagious disease is vital to avert further spread and to promptly treat the infected people. The need of automated scientific assisting diagnostic methods to identify Covid-19 in the infected people has increased since less accurate automated diagnostic methods are available. Recent studies based on the radiology imaging suggested that the imaging patterns on X-ray images and Computed Tomography (CT) scans contain leading information about Covid-19 and is considered as a potential automated diagnosis method. Machine learning and deep learning techniques combined with radiology imaging can be helpful for accurate detection of the disease. A deep learning approach based on the multilayer-Spatial Convolutional Neural Network for automatic detection of Covid-19 using chest X-ray images and CT scans is proposed in this paper. The proposed model, named as the Multilayer Spatial Covid Convolutional Neural Network (MSCovCNN), provides an automated accurate diagnostics for Covid-19 detection. The proposed model showed 93.63% detection accuracy and 97.88% AUC (Area Under Curve) for chest x-ray images and 91.44% detection accuracy and 95.92% AUC for chest CT scans, respectively. We have used 5-tiered 2D-CNN frameworks followed by the Artificial Neural Network (ANN) and softmax classifier. In the CNN each convolution layer is followed by an activation function and a Maxpooling layer. The proposed model can be used to assist the radiologists in detecting the Covid-19 and confirming their initial screening.https://www.ijimai.org/journal/bibcite/reference/2928coronavirus covid-19machine learningconvolution neural networkx-rayimagect scan |
| spellingShingle | Muhammad Irfan Khattak Mu’ath Al-Hasan Atif Jan Nasir Saleem Elena Verdú Numan Khurshid Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks International Journal of Interactive Multimedia and Artificial Intelligence coronavirus covid-19 machine learning convolution neural network x-ray image ct scan |
| title | Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks |
| title_full | Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks |
| title_fullStr | Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks |
| title_full_unstemmed | Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks |
| title_short | Automated Detection of COVID-19 using Chest X-Ray Images and CT Scans through Multilayer- Spatial Convolutional Neural Networks |
| title_sort | automated detection of covid 19 using chest x ray images and ct scans through multilayer spatial convolutional neural networks |
| topic | coronavirus covid-19 machine learning convolution neural network x-ray image ct scan |
| url | https://www.ijimai.org/journal/bibcite/reference/2928 |
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