A Novel Method COVID -19 infection using Deep Learning Based System

Coronavirus illness has infected millions of individuals globally and is contaminating them at an alarming rate, putting a strain on the health system's capabilities. PCR screening is the analytic technique of choice for COVID-19 discovery. CT imaging has demonstrated its diagnostic competence in asymptotic patients, establishing it as a reliable diagnostic support tool for COVID-19. The high prevalence of COVID-19 contaminations in CT slices enables the tracking of illness progression using automated contamination segmentation techniques. Nevertheless, COVID-19 infection regions exhibit a great degree of heterogeneity in terms of scale, form, contrast, and concentration, posing a substantial challenge to the segmentation approach. The present invention provides an automated segmentation technique based on deep learning for the discovery and delineation of COVID-19 infections in CT images. Additionally, as compared to existing techniques, this suggested innovation will need less time and money to identify the infection and annotate the infection regions. This innovation will assist physicians in determining the course of covid-19 illness, as well as quantifying the disease's load and severity, by segmenting the lung organ from the CT scan as a region of concern and then segmenting the infections contained inside it.