Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics

Impartially Validated Multiple Deep-Chain Models to Detect COVID-19 in Chest X-ray Using Latent Space Radiomics

The COVID-19 pandemic continues to spread globally at a rapid pace, and its rapid detection remains a challenge due to its rapid infectivity and limited testing availability. One of the simply available imaging modalities in clinical routine involves chest X-ray (CXR), which is often used for diagno...

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Bibliographic Details
Main Authors: Bardia Yousefi, Satoru Kawakita, Arya Amini, Hamed Akbari, Shailesh M. Advani, Moulay Akhloufi, Xavier P. V. Maldague, Samad Ahadian
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Journal of Clinical Medicine
Subjects:
COVID-19 detection
deep convolutional autoencoder (ConvAE)
2D U-Net model
imaging biomarker
deep-learning features
deep latent space radiomics
Online Access:https://www.mdpi.com/2077-0383/10/14/3100

Internet

https://www.mdpi.com/2077-0383/10/14/3100

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