SEGMENTATION AND DETECTION OF COVID-19 IN X-RAY IMAGES USING PARTICLE SWARM OPTIMIZATION

Abstract

The COVID-19 pandemic underscores the imperative for precise and efficient virus identification to avert its dissemination. Imaging studies of the chest are essential to ascertain the necessity for proper delineation of the affected region. This study suggests a segmentation method utilizing COVID-19 X-ray techniques implemented through Particle Swarm Optimization (PSO). The method needed X-ray images that had already been processed with Discrete Wavelet Transform (DWT) and PSO to find and separate the areas that were contaminated. The segmented images were successfully tested for accuracy. Our data indicate that the proposed technique successfully delineates the affected area, illustrating its potential utility in diagnosing COVID-19. This study helps make accurate and useful Screening for COVID-19 methods, which are very important for stopping the spread of the disease.