COVID-19 anomaly detection and classification method based on supervised machine learning of chest X-ray images

• Published in: Results in physics Vol. 31; p. 105045
• Main Authors: Hasoon, Jamal N., Fadel, Ali Hussein, Hameed, Rasha Subhi, Mostafa, Salama A., Khalaf, Bashar Ahmed, Mohammed, Mazin Abed, Nedoma, Jan
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2021; The Author(s). Published by Elsevier B.V; Elsevier
• Subjects: COVID-19 diagnosis; Haralick; K-nearest neighbor; Local binary pattern; Machine learning; Support vector machine; X-ray image; COVID-19 diagnosis; Local binary pattern; Machine learning; K-nearest neighbor; X-ray image; Support vector machine; Haralick

•We propose a method for early detection of COVID-19 through analysis of X-ray images.•The method performs preprocessing, RoI detection, segmentation, feature extraction, and classification steps.•The method contains six models, namely LBP-KNN, HOG-KNN, Haralick-KNN, LBP-SVM, HOG-SVM, and Haralick-S...