COVID-19 Classification in Chest CT Images Using Deep Convolution Neural Networks
| dc.contributor.author | Elgadi, Malek | |
| dc.contributor.supervisor | Gebali, Fayez | |
| dc.contributor.supervisor | El Miligi, Haytham | |
| dc.date.accessioned | 2022-11-15T02:04:58Z | |
| dc.date.available | 2022-11-15T02:04:58Z | |
| dc.date.copyright | 2022 | en_US |
| dc.date.issued | 2022-11-14 | |
| dc.degree.department | Department of Electrical and Computer Engineering | |
| dc.degree.level | Master of Engineering M.Eng. | en_US |
| dc.description.abstract | The coronavirus disease (COVID-19) has rapidly spread over the world since the end of 2019. The immediate and accurate diagnosis of COVID-19 is essential for improving the prognosis of this disease and reducing the pandemic spread. Although the PCR test is a standard test to diagnose COVID-19, radiography techniques such as chest X-rays and computed tomography (CT) scans are preferred for detection of COVID-19 disease. Deep learning and convolutional neural Networks (CNNs) play an important role in the early and accurate detection of COVID-19 using radiography images. In this project, a deep convolutional neural network framework based on a transfer learning technique with fine-tuning is suggested for detection and classification of COVID-19. Two pre-trained models i.e., VGG16 and DenseNet201 are trained using COVID-19 CT images dataset. Various experiments are performed to evaluate the performance of the pre-trained models using several evaluation parameters. The results show that the best accuracy of 99.4%, recall of 99.39%, precision of 99.4%, F1-score of 99.39%, and Area Under the Curve (AUC) of 99.93% are achieved by VGG-16 model. DenseNet201 model also shown a competitive result with an accuracy of 99.13 since it has lesser execution time and fewer parameters compared to other deep learning models. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/14469 | |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.title | COVID-19 Classification in Chest CT Images Using Deep Convolution Neural Networks | en_US |
| dc.type | project | en_US |