Computational Intelligence and Healthcare Informatics

17COVID-19 Detection System Using Cellular Automata–Based Segmentation Techniques

Rupashri Barik¹*, M. Nazma B. J. Naskar² and Sarbajyoti Mallik¹

¹Department of Information Technology JIS College of Engineering, Kalyani, W. B., India

²School of Computer Engineering, Kalinga Institute of Industrial Technology, Odisha, India

Abstract

In this pandemic situation, human lives are in stake, and it is very urgent to detect the infection earliest to save the lives. X-ray is the most common test among medical imaging modalities. X-ray is cheaper and faster to carry out the Computed Tomography (CT). As COVID-19 causes pneumonia in massive sense, the chest X-ray can help to identify whether the person is infected by novel Coronavirus or not. In this paper, we have proposed one automatic COVID-19 detection system that can be used as an alternative diagnosis medium of COVID-19 detection. Applying filter quality of image has been enhanced first. It may help to get a better contrast image depending on chest X-ray image. To detect the growth of infection in lungs, it is required to segment the infected region of lungs from its background. Cellular automata (CA) are very much effective for bio-medical image processing in terms of computation time and clarity. Henceforth, applying CA segmentation rules, here, we perform the lung segmentation and the segmented images to be compared with the chest X-ray of non-infected persons as well as with the chest X-ray of pneumonia infected person to determine ...