Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-Ray Images

Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-Ray Images

Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic capability when handling COVID-19. However, classifying COVID...

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Bibliographic Details
Main Authors: Jin, Q. (Author), Li, J. (Author), Liu, J. (Author), Sun, L. (Author), Wang, J. (Author), Wang, S. (Author), Wang, Y. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:
algorithm
Article
artificial intelligence
bacterial pneumonia
Chest X-ray image
Classification (of information)
Classification performance
computer assisted diagnosis
computer assisted tomography
controlled study
convolutional neural network
coronavirus disease 2019
COVID-19
deep learning
Deep learning
Deep Learning
deep neural network
diabetic retinopathy
Diagnosis
Diagnostic capabilities
diagnostic imaging
diagnostic test accuracy study
Distance regularizations
feature extraction
feature selection
Feature variations
human
Humans
image analysis
image segmentation
learning algorithm
lung
Lung
major clinical study
mathematical model
measurement accuracy
multiscale attention
multiscale attention guided network
Multi-scale features
nerve cell network
pleura effusion
pneumonia
positron emission tomography
Prediction vectors
procedures
Radiographic Image Interpretation, Computer-Assisted
Radiography, Thoracic
receiver operating characteristic
SARS-CoV-2
sensitivity and specificity
Spatial characteristics
thorax radiography
virus pneumonia
x-ray radiology
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