Abstract
At the end of 2019, a severe public health threat named coronavirus disease (COVID-19) spread rapidly worldwide. After two years, this coronavirus still spreads at a fast rate. Due to its rapid spread, the immediate and rapid diagnosis of COVID-19 is of utmost importance. In the global fight against this virus, chest X-rays are essential in evaluating infected patients. Thus, various technologies that enable rapid detection of COVID-19 can offer high detection accuracy to health professionals to make the right decisions. The latest emerging deep-learning (DL) technology enhances the power of medical imaging tools by providing high-performance classifiers in X-ray detection, and thus various researchers are trying to use it with limited success. Here, we propose a robust, lightweight network where excellent classification results can diagnose COVID-19 by evaluating chest X-rays. The experimental results showed that the modified architecture of the model we propose achieved very high classification performance in terms of accuracy, precision, recall, and f1-score for four classes (COVID-19, normal, viral pneumonia and lung opacity) of 21.165 chest X-ray images, and at the same time meeting real-time constraints, in a low-power embedded system. Finally, our work is the first to propose such an optimized model for a low-power embedded system with increased detection accuracy.
Highlights
COVID-19 is a highly contagious and infectious disease that causes severe infection of the lower respiratory system
The clinical findings of COVID-19 infection are those of bronchopneumonia, where cough, dyspnea, fever and respiratory failure with acute respiratory distress syndrome (ARDS) occur [3,4]
It is evident that our modified MobileNetV2 achieves much better results, classifying correctly many more images than the standard
Summary
COVID-19 is a highly contagious and infectious disease that causes severe infection of the lower respiratory system. COVID-19 was officially declared a global pandemic by the. The total number of COVID-19 cases worldwide up to this point, which changes almost every minute, is over 328 million, including 5 million deaths and 55 million active patients [2]. The increasing number of deaths from COVID-19 and the rapid rate of disease transmission makes it one of the world’s most significant and most serious public health issues. The clinical findings of COVID-19 infection are those of bronchopneumonia, where cough, dyspnea, fever and respiratory failure with acute respiratory distress syndrome (ARDS) occur [3,4]. Radiographic imaging is the fastest, cheapest, and most essential diagnostic tool for detecting pneumonia while providing lower patient radiation than computed tomography (CT) and magnetic resonance imaging (MRI) [5,6]
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