A Novel Classification Model Using Optimal Long Short-Term Memory for Classification of COVID-19 from CT Images

The human respiratory system is affected when an individual is infected with COVID-19, which became a global pandemic in 2020 and affected millions of people worldwide. However, accurate diagnosis of COVID-19 can be challenging due to small variations in typical and COVID-19 pneumonia, as well as th...

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Veröffentlicht in:	Journal of digital imaging Jg. 36; H. 6; S. 2480 - 2493
Hauptverfasser:	Vinothini, R, Niranjana, G, Yakub, Fitri
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Springer Nature B.V 01.12.2023
Schlagworte:	Algorithms Classification Computed tomography Coronaviruses COVID-19 COVID-19 - diagnostic imaging Deep learning Design standards Feature extraction Humans Image processing Image segmentation Long short-term memory Machine learning Medical imaging Network design Neural networks Neural Networks, Computer Optimization Pandemics Parameters Respiratory system Segmentation Tomography, X-Ray Computed Viral diseases Computerized tomography scan images Pelican optimization algorithm Coronavirus No new U-Net High-resolution net Disease prediction
ISSN:	0897-1889, 1618-727X, 1618-727X
Online-Zugang:	Volltext
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