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COVID-19 Diagnosis Using an Enhanced Inception-ResNetV2 Deep Learning Model in CXR Images
- Source :
- Journal of Healthcare Engineering, Vol 2021 (2021), Journal of Healthcare Engineering
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- The COVID-19 pandemic has a significant negative effect on people’s health, as well as on the world’s economy. Polymerase chain reaction (PCR) is one of the main tests used to detect COVID-19 infection. However, it is expensive, time-consuming, and lacks sufficient accuracy. In recent years, convolutional neural networks have grabbed many researchers’ attention in the machine learning field, due to its high diagnosis accuracy, especially the medical image recognition. Many architectures such as Inception, ResNet, DenseNet, and VGG16 have been proposed and gained an excellent performance at a low computational cost. Moreover, in a way to accelerate the training of these traditional architectures, residual connections are combined with inception architecture. Therefore, many hybrid architectures such as Inception-ResNetV2 are further introduced. This paper proposes an enhanced Inception-ResNetV2 deep learning model that can diagnose chest X-ray (CXR) scans with high accuracy. Besides, a Grad-CAM algorithm is used to enhance the visualization of the infected regions of the lungs in CXR images. Compared with state-of-the-art methods, our proposed paper proves superiority in terms of accuracy, recall, precision, and F1-measure.
- Subjects :
- Medicine (General)
Article Subject
Coronavirus disease 2019 (COVID-19)
Computer science
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Pneumonia, Viral
Biomedical Engineering
Health Informatics
Machine learning
computer.software_genre
Residual
Convolutional neural network
Residual neural network
Field (computer science)
030218 nuclear medicine & medical imaging
Diagnosis, Differential
03 medical and health sciences
Deep Learning
0302 clinical medicine
R5-920
Medical technology
Humans
R855-855.5
Lung
030304 developmental biology
0303 health sciences
SARS-CoV-2
business.industry
Deep learning
COVID-19
Visualization
Radiographic Image Interpretation, Computer-Assisted
Radiography, Thoracic
Surgery
Artificial intelligence
business
computer
Algorithms
Research Article
Biotechnology
Subjects
Details
- Language :
- English
- ISSN :
- 20402309 and 20402295
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Journal of Healthcare Engineering
- Accession number :
- edsair.doi.dedup.....1a17c1673efa69c1b3ad92fe2b43ecdf