Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images

Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbreak. However, radiologists have to distinguish COVID-19 pneumonia from other pneumonia in a large number of CT scans, which is tedious and inefficient....

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics Jg. 19; H. 5; S. 2723 - 2736
Hauptverfasser:	Cheng, Jianhong, Zhao, Wei, Liu, Jin, Xie, Xingzhi, Wu, Shangjie, Liu, Liangliang, Yue, Hailin, Li, Junjian, Wang, Jianxin, Liu, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.09.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Computed tomography Coronaviruses COVID-19 deep supervised autoencoder Diagnosis Diagnostic software Feature extraction Hospitals Lesions Medical imaging multi-task learning multi-view features Patients Pneumonia Pulmonary diseases Three-dimensional displays Viral diseases
ISSN:	1545-5963, 1557-9964, 1557-9964
Online-Zugang:	Volltext
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