A Review on Deep Learning Methods and CT Scan Approaches for Covid-19 Detection

Abstract

Now-a-days, we all face pandemic infectious disease COVID-19, i.e. coronavirus disease. This disease is precarious because it is transmitted efficiently by close or far with a contaminated person. In this coronavirus disease pandemic, a lot of infected citizens increase every day. The only way to retard the speed of spreading this infectious virus is to recognize and examine this pandemic COVID - 19 disease. The Real-Time Reverse Transcription Polymerase Chain Reaction (RT-PCR) is used as a primary testing approach to diagnose coronavirus disease. However, the RT-PCR detection method is a highly-priced and drawn-out process. Thus, there is a need to design other ways to detect and diagnose COVID-19. The essential part of data-driven science is deep learning. In machine learning, we have to choose properties and images, whereas, in deep learning modeling, the extraction of data step is done automatically. Data learning is the upgrade version of machine learning. Deep learning is used to converge with the convolutional neural network (CNN), mainly accustomed to detecting the disease. This paper will explain the basics of deep learning (DL) techniques and their application in this COVID-19 pandemic situation. For an accurate diagnosis, precise tracking of infection development performs a crucial function. In COVID-19, the computer tomography CT is used for keeping an eye on continuous monitoring of disease development. In most countries, computed tomography is an inexpensive test that helps diagnose covid-19 detection. This paper will also enlist the aspects of CT scan techniques used to recognize coronavirus disease.

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