Analysis Of The Corona Virus And Identification Of This Virus Using Deep Learning

Today, the new corona virus has become a major global epidemic. Every day, a high percentage of the entire world's population gets infected with this virus, and a significant percentage die as a result of the infection. Due to the highly infectious nature of this virus, timely diagnosis, treatment and quarantine are considered essential. Corona disease, which started in China, has affected more than 480 million cases worldwide. Due to the limited number of test kits and the time-consuming nature of diagnosis, CT scan and X-ray chest radiography can be used as alternative rapid diagnostic options. The World Health Organization has recommendations for timely diagnosis of the disease of Covid-19 in order to adopt the appropriate treatment. CT images and deep learning algorithms will be used in this study to diagnose COVID-19. First, a new approach to removing noise from CT images is presented using wavelet transformation and fuzzy logic. The combined global and local threshold method was then used to segment lung images. As a result, lung regions can be successfully segmented from CT images. The next step will be the extraction of features and classifications. Feature extraction is carried out by Alex Net, while classification is carried out by Support Vector Machines (SVM).

Analysis Of The Corona Virus And Identification Of This Virus Using Deep Learning Keywords:

Corona virus , diagnosis , deep learning , chest , CT