A Comparative and Extensive Study of Covid 19 Diagnosis using Lung Ultrasound Images

Abstract

The COVID-19 pandemic has resulted in a worldwide health crisis that has affected all facets of human existence and has brought the world to a halt. The most important pre-requisite for COVID-19 diagnosis is early detection. Ma-chine learning algorithms can help in speeding up the process while saving money and effort. Following a comprehensive background study on the various medical imaging options available, it was discovered that there are few surveys focus-ing on COVID-19 identification based on Lung Ultrasound. The feasibility of lung ultrasound is visible from the sur-vey. In this paper, huge efforts have been undertaken to study the road-map of lung ultrasound markers for detect-ing COVID-19. The detection of abnormal A lines, B lines and pleural lines or traces in ultrasound images will aid in the rapid identification and control of the ongoing COVID-19 epidemic. The numerous deep learning models will make diagnosis easier and more accurate, assisting doctors and front-line employees in this pandemic emergency.