Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach
COVID-19 is a disease caused by the SARS-CoV-2 virus. The COVID-19 virus spreads when a person comes into contact with an affected individual. This is mainly through drops of saliva or nasal discharge. Most of the affected people have mild symptoms while some people develop acute respiratory distres...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/5/895 |
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| author | Yash Karbhari Arpan Basu Zong Woo Geem Gi-Tae Han Ram Sarkar |
| author_facet | Yash Karbhari Arpan Basu Zong Woo Geem Gi-Tae Han Ram Sarkar |
| author_sort | Yash Karbhari |
| collection | DOAJ |
| description | COVID-19 is a disease caused by the SARS-CoV-2 virus. The COVID-19 virus spreads when a person comes into contact with an affected individual. This is mainly through drops of saliva or nasal discharge. Most of the affected people have mild symptoms while some people develop acute respiratory distress syndrome (ARDS), which damages organs like the lungs and heart. Chest X-rays (CXRs) have been widely used to identify abnormalities that help in detecting the COVID-19 virus. They have also been used as an initial screening procedure for individuals highly suspected of being infected. However, the availability of radiographic CXRs is still scarce. This can limit the performance of deep learning (DL) based approaches for COVID-19 detection. To overcome these limitations, in this work, we developed an Auxiliary Classifier Generative Adversarial Network (ACGAN), to generate CXRs. Each generated X-ray belongs to one of the two classes COVID-19 positive or normal. To ensure the goodness of the synthetic images, we performed some experimentation on the obtained images using the latest Convolutional Neural Networks (CNNs) to detect COVID-19 in the CXRs. We fine-tuned the models and achieved more than 98% accuracy. After that, we also performed feature selection using the Harmony Search (HS) algorithm, which reduces the number of features while retaining classification accuracy. We further release a GAN-generated dataset consisting of 500 COVID-19 radiographic images. |
| first_indexed | 2024-03-10T11:19:09Z |
| format | Article |
| id | doaj.art-7d4c409c01e24cfeba05c2f5543f8160 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T11:19:09Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-7d4c409c01e24cfeba05c2f5543f81602023-11-21T20:11:20ZengMDPI AGDiagnostics2075-44182021-05-0111589510.3390/diagnostics11050895Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based ApproachYash Karbhari0Arpan Basu1Zong Woo Geem2Gi-Tae Han3Ram Sarkar4Department of Information Technology, Pune Vidyarthi Griha’s College of Engineering and Technology, Pune 411009, IndiaDepartment of Computer Science and Engineering, Jadavpur University, Kolkata 700032, IndiaCollege of IT Convergence, Gachon University, 1342 Seongnam Daero, Seongnam 13120, KoreaCollege of IT Convergence, Gachon University, 1342 Seongnam Daero, Seongnam 13120, KoreaDepartment of Computer Science and Engineering, Jadavpur University, Kolkata 700032, IndiaCOVID-19 is a disease caused by the SARS-CoV-2 virus. The COVID-19 virus spreads when a person comes into contact with an affected individual. This is mainly through drops of saliva or nasal discharge. Most of the affected people have mild symptoms while some people develop acute respiratory distress syndrome (ARDS), which damages organs like the lungs and heart. Chest X-rays (CXRs) have been widely used to identify abnormalities that help in detecting the COVID-19 virus. They have also been used as an initial screening procedure for individuals highly suspected of being infected. However, the availability of radiographic CXRs is still scarce. This can limit the performance of deep learning (DL) based approaches for COVID-19 detection. To overcome these limitations, in this work, we developed an Auxiliary Classifier Generative Adversarial Network (ACGAN), to generate CXRs. Each generated X-ray belongs to one of the two classes COVID-19 positive or normal. To ensure the goodness of the synthetic images, we performed some experimentation on the obtained images using the latest Convolutional Neural Networks (CNNs) to detect COVID-19 in the CXRs. We fine-tuned the models and achieved more than 98% accuracy. After that, we also performed feature selection using the Harmony Search (HS) algorithm, which reduces the number of features while retaining classification accuracy. We further release a GAN-generated dataset consisting of 500 COVID-19 radiographic images.https://www.mdpi.com/2075-4418/11/5/895COVID-19 detectiongenerative adversarial networksynthetic data generationharmony searchfeature selectionchest X-ray |
| spellingShingle | Yash Karbhari Arpan Basu Zong Woo Geem Gi-Tae Han Ram Sarkar Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach Diagnostics COVID-19 detection generative adversarial network synthetic data generation harmony search feature selection chest X-ray |
| title | Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach |
| title_full | Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach |
| title_fullStr | Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach |
| title_full_unstemmed | Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach |
| title_short | Generation of Synthetic Chest X-ray Images and Detection of COVID-19: A Deep Learning Based Approach |
| title_sort | generation of synthetic chest x ray images and detection of covid 19 a deep learning based approach |
| topic | COVID-19 detection generative adversarial network synthetic data generation harmony search feature selection chest X-ray |
| url | https://www.mdpi.com/2075-4418/11/5/895 |
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