Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Article
Sharifrazi, Danial, Alizadehsani, Roohallah, Roshanzamir, Mohamad, Joloudari, Javad Hassannataj, Shoeibi, Afshin, Jafari, Mahboobeh, Hussain, Sadiq, Sani, Zahra Alizade, Hasanzadeh, Fereshteh, Khozeimeh, Fahime, Khosravi, Abbas, Nahavandi, Saeid, Panahiazar, Maryam, Zare, Assef, Islam, Sheikh Mohammed Shariful and Acharya, U. Rajendra. 2021. "Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images." Biomedical Signal Processing and Control. 68. https://doi.org/10.1016/j.bspc.2021.102622
| Article Title | Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images |
|---|---|
| ERA Journal ID | 3391 |
| Article Category | Article |
| Authors | Sharifrazi, Danial, Alizadehsani, Roohallah, Roshanzamir, Mohamad, Joloudari, Javad Hassannataj, Shoeibi, Afshin, Jafari, Mahboobeh, Hussain, Sadiq, Sani, Zahra Alizade, Hasanzadeh, Fereshteh, Khozeimeh, Fahime, Khosravi, Abbas, Nahavandi, Saeid, Panahiazar, Maryam, Zare, Assef, Islam, Sheikh Mohammed Shariful and Acharya, U. Rajendra |
| Journal Title | Biomedical Signal Processing and Control |
| Journal Citation | 68 |
| Article Number | 102622 |
| Number of Pages | 14 |
| Year | 2021 |
| Publisher | Elsevier |
| Place of Publication | Netherlands |
| ISSN | 1746-8094 |
| Digital Object Identifier (DOI) | https://doi.org/10.1016/j.bspc.2021.102622 |
| Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1746809421002196 |
| Abstract | The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to prevent secondary infections and its spread from one person to another. Therefore, it is essential to use an automatic diagnosis system along with clinical procedures for the rapid diagnosis of COVID-19 to prevent its spread. Artificial intelligence techniques using computed tomography (CT) images of the lungs and chest radiography have the potential to obtain high diagnostic performance for Covid-19 diagnosis. In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images. A new X-ray image dataset was collected and subjected to high pass filter using a Sobel filter to obtain the edges of the images. Then these images are fed to CNN deep learning model followed by SVM classifier with ten-fold cross validation strategy. This method is designed so that it can learn with not many data. Our results show that the proposed CNN-SVM with Sobel filter (CNN-SVM + Sobel) achieved the highest classification accuracy, sensitivity and specificity of 99.02%, 100% and 95.23%, respectively in automated detection of COVID-19. It showed that using Sobel filter can improve the performance of CNN. Unlike most of the other researches, this method does not use a pre-trained network. We have also validated our developed model using six public databases and obtained the highest performance. Hence, our developed model is ready for clinical application. |
| Keywords | CNN; Image processing ; Data mining ; Machine learning ; Deep learning ; Feature extraction ; Covid-19 ; Sobel operator ; SVM |
| ANZSRC Field of Research 2020 | 400306. Computational physiology |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | Islamic Azad University, Iran |
| Deakin University | |
| Fasa University, Iran | |
| University of Birjand, Iran | |
| Ferdowsi University of Mashhad, Iran | |
| K. N. Toosi University of Technology, Iran | |
| Semnan University, Iran | |
| Dibrugarh University, India | |
| Iran University of Medical Sciences, Iran | |
| University of California, United States | |
| George Institute for Global Health, Australia | |
| University of Sydney | |
| Ngee Ann Polytechnic, Singapore | |
| Singapore University of Social Sciences (SUSS), Singapore | |
| Asia University, Taiwan |
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