Analysis of CT scan images for COVID-19 pneumonia based on a deep ensemble framework with DenseNet, Swin transformer, and RegNet

Analysis of CT scan images for COVID-19 pneumonia based on a deep ensemble framework with DenseNet, Swin transformer, and RegNet

COVID-19 has caused enormous challenges to global economy and public health. The identification of patients with the COVID-19 infection by CT scan images helps prevent its pandemic. Manual screening COVID-19-related CT images spends a lot of time and resources. Artificial intelligence techniques inc...

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Bibliographic Details
Main Authors: Lihong Peng, Chang Wang, Geng Tian, Guangyi Liu, Gan Li, Yuankang Lu, Jialiang Yang, Min Chen, Zejun Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Microbiology
Subjects:
COVID-19 pneumonia
CT scan image
deep ensemble
DenseNet
Swin transformer
RegNet
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2022.995323/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2022.995323/full

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