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Automated detection of COVID-19 from CT scan using convolutional neural network
- Source :
- Biocybernetics and Biomedical Engineering
- Publication Year :
- 2021
- Publisher :
- Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V., 2021.
-
Abstract
- Under the prevailing circumstances of the global pandemic of COVID-19, early diagnosis and accurate detection of COVID-19 through tests/screening and, subsequently, isolation of the infected people would be a proactive measure. Artificial intelligence (AI) based solutions, using Convolutional Neural Network (CNN) and exploiting the Deep Learning model's diagnostic capabilities, have been studied in this paper. Transfer Learning approach, based on VGG16 and ResNet50 architectures, has been used to develop an algorithm to detect COVID-19 from CT scan images consisting of Healthy (Normal), COVID-19, and Pneumonia categories. This paper adopts data augmentation and fine-tuning techniques to improve and optimize the VGG16 and ResNet50 model. Further, stratified 5-fold cross-validation has been conducted to test the robustness and effectiveness of the model. The proposed model performs exceptionally well in case of binary classification (COVID-19 vs. Normal) with an average classification accuracy of more than 99% in both VGG16 and ResNet50 based models. In multiclass classification (COVID-19 vs. Normal vs. Pneumonia), the proposed model achieves an average classification accuracy of 86.74% and 88.52% using VGG16 and ResNet50 architectures as baseline, respectively. Experimental results show that the proposed model achieves superior performance and can be used for automated detection of COVID-19 from CT scans.
- Subjects :
- Computer science
0206 medical engineering
Biomedical Engineering
Convolutional Neural Network
02 engineering and technology
Convolutional neural network
Multiclass classification
CT scan images
Robustness (computer science)
0202 electrical engineering, electronic engineering, information engineering
Isolation (database systems)
Original Research Article
Measure (data warehouse)
business.industry
Deep learning
COVID-19
Pattern recognition
020601 biomedical engineering
Transfer learning
Binary classification
020201 artificial intelligence & image processing
VGG16
Artificial intelligence
Transfer of learning
business
ResNet50
Subjects
Details
- Language :
- English
- ISSN :
- 02085216
- Volume :
- 41
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Biocybernetics and Biomedical Engineering
- Accession number :
- edsair.doi.dedup.....91c438609c550694520d6b55c901af01