Optimal Diagnosis of COVID-19 Based on Convolutional Neural Network and Red Fox Optimization Algorithm.

Ehsan Khorami,Aidin Azadeh,Fatemeh Mahdi Babaei,Navid Razmjooy

doi:10.1155/2021/4454507

Abstract

SARS-CoV-2 is a specific type of Coronavirus that was firstly reported in China in December 2019 and is the causative agent of coronavirus disease 2019 (COVID-19). In March 2020, this disease spread to different parts of the world causing a global pandemic. Although this disease is still increasing exponentially day by day, early diagnosis of this disease is very important to reduce the death rate and to reduce the prevalence of this pandemic. Since there are sometimes human errors by physicians in the diagnosis of this disease, using computer-aided diagnostic systems can be helpful to get more accurate results. In this paper, chest X-ray images have been examined using a new pipeline machine vision-based system to provide more accurate results. In the proposed method, after preprocessing the input X-ray images, the region of interest has been segmented. Then, a combined gray-level cooccurrence matrix (GLCM) and Discrete Wavelet Transform (DWT) features have been extracted from the processed images. Finally, an improved version of Convolutional Neural Network (CNN) based on the Red Fox Optimization algorithm is employed for the classification of the images based on the features. The proposed method is validated by performing to three datasets and its results are compared with some state-of-the-art methods. The final results show that the suggested method has proper efficiency toward the others for the diagnosis of COVID-19.

Highlights

Coronaviruses are a large family of viruses that can cause disease in animals or humans
Results and Discussions e proposed method proposes an effective automated method for automatic diagnosis of the COVID-19 based on hybridizing the convolutional neural network and Red Fox Optimization algorithm. e method is a pipeline technique including preprocessing, segmentation, features extraction, and classification
COVID-19 is a new member of coronaviruses named by the World Health Organization (WHO) on February 11, 2020, based on the year of its outbreak and its infectious agent

Summary

Introduction

Coronaviruses are a large family of viruses that can cause disease in animals or humans. Several types of viruses cause respiratory infections, from the common cold to more serious illnesses such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). A recently discovered virus from this family is SARSCoV-2. It causes an infectious disease that has recently been discovered. People can get COVID-19 from other infected people with the virus. E disease can be spread from person to person with small drops in the nose or mouth when coughing or exhaling. Other people catch COVID19 by touching these objects or surfaces and touch their eyes, nose, or mouth. People can get COVID-19 if they breathe in drops from a person with COVID-19 who coughs

Methods

Results

Conclusion