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Coronavirus disease 2019 (COVID-19), a microbial infection, is induced by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Automatic computer-aided detection can help detect the infected patients using chest imaging i.e., CXR and CT scans. This paper proposes a method to detect infected patients with high accuracy using chest X-ray image of a patient. It proposes a model that includes deep model features and Local Binary Pattern (LBP) features along with Support Vector Machine (SVM) classifier. The model is utilized for binary classification among normal and COVID-19 infected patients X-rays. Proposed model produced 99.4% accuracy using VGG16 deep features along with LBP features and the Gaussian SVM classifier.
Inspec keywords: image texture; diseases; diagnostic radiography; image classification; patient diagnosis; support vector machines; pattern classification; feature extraction; molecular biophysics; computerised tomography; microorganisms; medical image processing
Subjects: Optical and laser radiation (medical uses); X-rays and particle beams (medical uses); Biology and medical computing; Computer vision and image processing techniques; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Patient diagnostic methods and instrumentation; Other topics in statistics; Optical, image and video signal processing; Biomedical measurement and imaging; Biomedical engineering; Optical and laser radiation (biomedical imaging/measurement); Other topics in statistics