Coronavirus Pneumonia Classification Using X-Ray and CT Scan Images With Deep Convolutional Neural Network Models

Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans. There are mainly two types of pneumonia: bacterial and viral. Likewise, patients with coronavirus can develop symptoms that belong to the common flu, pneumonia, and other respiratory diseases. Chest x-rays are the common method used to diagnose coronavirus pneumonia, and it needs a medical expert to evaluate the result of x-ray. Furthermore, DL has garnered great attention among researchers in recent years in a variety of application domains such as medical image processing, computer vision, bioinformatics, and many others. This work represents a comparison of deep convolutional neural networks models for automatically binary classification query chest x-ray and CT images dataset with the goal of taking precision tools to health professionals based on fined recent versions of ResNet50, InceptionV3, and VGGNet. The experiments were conducted using a chest x-ray and CT open dataset of 5,856 images, and confusion matrices are used to evaluate model performances.