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Optimized chest X-ray image semantic segmentation networks for COVID-19 early detection
2022
Journal of X-Ray Science and Technology
BACKGROUND: Although detection of COVID-19 from chest X-ray radiography (CXR) images is faster that PCR sputum testing, the accuracy of detecting COVID-19 from CXR images is lacking in the existing deep learning models. OBJECTIVE: This study aims to classify COVID-19 and normal patients from CXR images using semantic segmentation networks for detecting and labeling COVID-19 infected lung lobes in CXR images. METHODS: For semantically segmenting infected lung lobes in CXR images for COVID-19
doi:10.3233/xst-211113
pmid:35213339
fatcat:flrz76hj4fazppwv3x4invs5v4