Classification of Chest X-ray Images using Convolutional Neural Nework

¹ Information Technology Prince Shri Venkateshwara Padmava1thy Engineering College, Chennai, Tamil Nadu
² Mechanical Engineering Department, PNG University of Technology, Papua New Guinea
³ Tashkent State Pedagogical University, Tashkent, Uzbekistan
⁴ Mohammed Satak Engineering College, Ramnad, Tamilnadu, India

^* Corresponding Authour: allirani.p.cse@psvpec.in
aezeden.mohamed@pnguot.ac.pg
abdulaziz9333.aa@gmail.com

Abstract

The current worldwide Covid-19 epidemic is linked to a respiratory lung infection caused by a novel corona virus disease (SARSCoV- 2), the evolution of which is still not known. More than 100,000 cases were confirmed worldwide using the current case definition of Covid-19 infection, based on pneumonia diagnosis, with a death rate ranging between 2% and 3%. Since the expanding sick population might not have simple access to current laboratory testing, new screening techniques are necessary. The Computed tomography of chest is an important technique for the former detection and treatment of Covid-19 pulmonary symptoms, even though its utility as a screening tool has not yetbeen established. Even though it lacked specificity, it exhibited excellent sensitivity. We demonstrate a neural network based on pneumonia and covid classification in Tensor Flow and Keras. The suggested method is based on the CNN uses images and the CNN model to categorize Covid-19 or pneumonia. It is anticipated that discoveries will become more successful. If the covid-19 or pneumonia classification algorithms and other feature extraction methods are added, the CNN approach will be successfully supported.