Automated COVID-19 Detection with Ensemble Deep Convolution Neural Networks using Computed Tomography Images

The recently identified presence of the novel coronavirus (COVID-19) has had disastrous effects, and the World Health Organization (WHO) has declared it a serious worldwide pandemic. A person’s contact with the virus must be discovered as soon as possible to begin treatment and quarantine (if necessary) and prevent the virus from spreading to others in good health. This is equally as crucial as identifying the disease’s root cause. In this study, we will investigate the use of various models based on Deep Learning (DL) techniques for the purpose of screening COVID-19, as well as the advantages and drawbacks of these methods in contrast with others. We will look into the potential value of this imaging method for the management and early treatment of COVID-19 patients and review recent research studies that examined the accuracy and reliability of various pre-processing methods and models on chest CT scans for COVID-19 diagnosis.