Hybrid feature extraction technique for automatic classification of COVID-19 chest CT images
Author:
Affiliation:
1. Henan University of Science and Technology, Luoyang, Henan Province, China
2. Department of Neurology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, Henan Province, China
Funder
China Postdoctoral Science Foundation
National Natural Science Foundation of China
Medical and Health Research Project in Luoyang
Construction Project of Improving Medical Service Capacity of Provincial Medical Institutions in Henan Province
Project of Luoyang Science and Technology Bureau
Publisher
Informa UK Limited
Subject
Computer Science Applications,Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Computational Mechanics
Link
https://www.tandfonline.com/doi/pdf/10.1080/21681163.2023.2250861
Reference48 articles.
1. Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
2. A novel data augmentation based on Gabor filter and convolutional deep learning for improving the classification of COVID-19 chest X-Ray images
3. Transfer learning-based approach for detecting COVID-19 ailment in lung CT scan
4. Spatial Context Energy Curve-Based Multilevel 3-D Otsu Algorithm for Image Segmentation
5. Performance of an alternative RT-PCR procedure using residual sample from the Panbio™ Ag COVID-19 test
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