Abstract
Coronavirus pandemic (COVID-19) has infected more than ten million persons worldwide. Therefore, researchers are trying to address various aspects that may help in diagnosis this pneumonia. Image segmentation is a necessary pr-processing step that implemented in image analysis and classification applications. Therefore, in this study, our goal is to present an efficient image segmentation method for COVID-19 Computed Tomography (CT) images. The proposed image segmentation method depends on improving the density peaks clustering (DPC) using generalized extreme value (GEV) distribution. The DPC is faster than other clustering methods, and it provides more stable results. However, it is difficult to determine the optimal number of clustering centers automatically without visualization. So, GEV is used to determine the suitable threshold value to find the optimal number of clustering centers that lead to improving the segmentation process. The proposed model is applied for a set of twelve COVID-19 CT images. Also, it was compared with traditional k-means and DPC algorithms, and it has better performance using several measures, such as PSNR, SSIM, and Entropy.
Highlights
Coronavirus (COVID-19) that first reported in December 2019, in Wuhan, China, has been spread to more than 200 countries and regions
We show the results of the proposed methods against the classical algorithm density peaks clustering (DPC) and K-means algorithm; these algorithms are widely used for processing medical images and clustering fields
We can see that the proposed method produced better segmentation results in most of the images. These results indicate that the proposed method can efficiently segment the chest Computed Tomography (CT) images with COVID-19
Summary
Coronavirus (COVID-19) that first reported in December 2019, in Wuhan, China, has been spread to more than 200 countries and regions. It could be transmitted through the respiratory droplets and the contact [1, 2]. The real-time polymerase chain reaction (RT-PCR) can be used to diagnose COVID-19, but it is a time-consuming test; it may suffer from false-negative diagnosing [4, 5]. Medical imaging, such as chest X-ray and chest Computed Tomography (CT) can be used efficiently for diagnosing COVID-19.
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