Corona Virus Recognition Using Chest X-Ray

The new coronavirus, or COVID-19, is a severe respiratory infection caused by the SARS-CoV-2 virus. The pandemic began in Wuhan, China in late 2019 and quickly spread globally, resulting in widespread illness, death, and major disruptions to economies and societies. The virus mainly spreads via respiratory droplets, and typical symptoms include fatigue, fever, coughing, and shortness of breath. While some individuals may have mild symptoms, others can develop severe illness and potentially fatal complications. The COVID-19 pandemic has prompted widespread efforts to slow it’s spread, including lockdowns, social distancing measures, and widespread use of personal protective equipment. Efforts to mitigate the impact of COVID-19 are ongoing, including research into treatments and vaccines. It becomes even more crucial in countries where laboratory kits is unavailable for testing. So, to diagnose COVID-19 disease, we tested a model built upon image processing as well as deep learning approaches. A COVID-19 infection could proceed to pneumonia, which could be diagnosed and treated with a chest X-ray. Here, we can create a dataset with 1403 chest X-rays. The dataset is loaded when the chest CT scans from COVID-19 have been acquired. We first propose pre-processing methods, use Image Augmentation, then make use of CT scans to determine whether or not COVID-19 (chest x-ray images) is positive or negative. Using deep learning to interpret images implementations are employed to achieve this.