A Novel Ct Image De-noising And Fusion Based Deep Learning Network To Screen For Disease (covid-19)

COVID-19 is a global pandemic caused by SARS-CoV-2, first discovered in China in December 2019. To combat the virus, reliable, accurate, and fast methods are urgently needed. Computer Tomography (CT) has been observed to be a subtle approach to detecting COVID-19, and it may be the best screening method. A novel Impulse and Poisson noise reduction method employing boundary division max/min intensities elimination along with an adaptive window size mechanism is proposed to improve the quality of the acquired image for post segmentation. A number of CNN techniques are explored for detecting COVID-19 from CT images and an Assessment Fusion Based model is proposed to predict the result.