T. Ahila, A C Subhajini
The COVID-19 pandemic has brought about the need for accurate and efficient detection of the virus to curb its spread. One approach is the use of chest X-rays for diagnosis, which requires accurate segmentation of the infected area. In this study, we propose a COVID-19 X-ray segmentation approach using Particle Swarm Optimization (PSO). The methodology involved preprocessing the X-ray images using Discrete Wavelet Transform (DWT), followed by PSO-based segmentation of the infected area. The segmented images were then quantitatively evaluated for accuracy. Our findings demonstrated that the suggested method successfully segmented the affected region, indicating its potential for use in COVID-19 diagnosis. This study contributes to the development of efficient and accurate COVID-19 detection approaches, which are essential in controlling the spread of the virus.
Covid-19,X-ray, Particle Swam Optimization, Discrete Wavelet Transform