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About An efficient method of detection of COVID-19 using Mask R-CNN on chest X-Ray images
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 X-ray 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 AI-based 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.
Detailed Information
| Author: | Soumyajit Podder & Somnath Bhattacharjee & Arijit Roy |
|---|---|
| Publication Year: | 2021 |
| Pages: | 10 |
| Language: | other |
| File Size: | 0.6962 |
| Format: | |
| Price: | FREE |
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