Detecting COVID_19 in X-ray images using artificial neural network

L. Prinza; G. Jerald Prasath

International Journal of Broadband Cellular Communication

Detecting COVID_19 in X-ray images using artificial neural network

Abstract

In this paper, we propose a method for detecting COVID-19, which is most important for now days in lowering mortality rates. COVID-19 had a rapid impact on our daily lives, businesses, and global trade and transportation. Chest CT scans and CT x-rays reveal particular radiographic abnormalities in people with COVID-19 by means of faster and more efficient representation of the patient's lung that enables for the detection of viral phenomena. Preprocessing the CT image to remove undesirable noises found in medical images is the first stage in our procedure. After that, Discrete Wavelet Transform based decomposition was done to exhibit the significant information from the image. Then the features are extracted from the coefficients and are trained in feed forward neural network to classify normal and COVID-19 patients. In this article a classification rate of about 85% is obtained.

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Detecting COVID_19 in X-ray images using artificial neural network

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