Swin-textural: A novel textural features-based image classification model for COVID-19 detection on chest computed tomography

Swin-textural: A novel textural features-based image classification model for COVID-19 detection on chest computed tomography

Background: Chest computed tomography (CT) has a high sensitivity for detecting COVID-19 lung involvement and is widely used for diagnosis and disease monitoring. We proposed a new image classification model, swin-textural, that combined swin-based patch division with textual feature extraction for...

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Bibliographic Details
Main Authors: Ilknur Tuncer, Prabal Datta Barua, Sengul Dogan, Mehmet Baygin, Turker Tuncer, Ru-San Tan, Chai Hong Yeong, U. Rajendra Acharya
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Swin
Textural feature extraction
Swin-textural
COVID-19 classification
Computed tomography images
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914822002957

Internet

http://www.sciencedirect.com/science/article/pii/S2352914822002957

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