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An efficient method of detection of COVID-19 using Mask R-CNN on chest X-Ray images.
- Source :
-
AIMS Biophysics . 2021, Vol. 8 Issue 3, p281-290. 10p. - Publication Year :
- 2021
-
Abstract
- Artificial intelligence techniques are used on chest X-ray images for accurate detection of diseases and this paper aims to develop a process which is capable of diagnosing COVID-19 using deep learning methods on X-ray images. For this purpose, we used Mask R-CNN method to train and test on the dataset to classify between patients infected and non-infected with COVID-19. The dataset used here contains a large number of frontal views of X-ray images which are an essential resource for the algorithms used in the development of tools for the detection of COVID-19. Using 668 chest Xray images, the proposed model achieved an accuracy as high as 96.98%, specificity of 97.36% with the precision of 96.60%. The entire process is presented in detail. When a comparison table on the AIbased techniques is prepared, it is noticed that the Mask R-CNN technique on chest X-ray images provides better efficiency in the detection of COVID-19. The Mask R-CNN method is found to be accurate and robust in the detection of COVID-19 from chest X-ray images. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 23779098
- Volume :
- 8
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- AIMS Biophysics
- Publication Type :
- Academic Journal
- Accession number :
- 152671105
- Full Text :
- https://doi.org/10.3934/biophy.2021022