Fractal based automatic detection of complexity in COVID‐19 X‐ray images

Author:

Thangaraj C.12,Easwaramoorthy D.1ORCID,Muhiuddin G.3,Selmi Bilel4,Kulish Vladimir5ORCID

Affiliation:

1. Department of Mathematics, School of Advanced Sciences Vellore Institute of Technology Vellore Tamil Nadu India

2. Department of Mathematics and Statistics School of Applied Sciences & Humanities, Vignan's Foundation for Science, Technology & Research Guntur Andhra Pradesh India

3. Department of Mathematics, Faculty of Science University of Tabuk Tabuk Saudi Arabia

4. Analysis, Probability & Fractals Laboratory: LR18ES17, Department of Mathematics, Faculty of Sciences of Monastir University of Monastir Monastir Tunisia

5. Department of Computer Science, Faculty of Science University of South Bohemia in Ceske Budejovice Branisovska Ceske Budejovice Czech Republic

Abstract

AbstractThe coronavirus was discovered in Wuhan, China, in December 2019. Scientists and medical practitioners have warned that this fatal virus could spread quickly from person to person in its early stages and its impact will be far more vigorous than the previously discovered viruses. The World Health Organization has given warning propaganda to all nations about this harmful virus. However, the diffusion speed of COVID‐19 was so rapid that it spread to all countries much faster than the researchers predicted, causing the widespread human disaster. The genetic variations of COVID‐19 have also astounded researchers today, as it modifies its mutation with very large genetic strains. The virus is regarded as a human version of the disease, resulting in the common cold, dry cough, and respiratory problems in severe cases. According to health organisations, the coronavirus directly affects the lungs, causing main problems such as difficulty breathing. It is also tough for physicians to diagnose the disease level properly by using the regular process. Even though the virus can be detected in regular testing methods, even computed tomography (CT) and X‐ray images are widely used in the medical field to identify the respiratory problems caused by the COVID‐19 virus. Like COVID‐19, some other types of pneumonia respiratory diseases also affect the human lungs. The fractal dimension (FD) is an interesting non‐linear measure to describe the complexity of visual images. In this context, the complexity of X‐ray images is analysed by using the fractal dimension. The fractal dimension is an excellent non‐linear measurement for describing the complexity of realistic images. The difference between the complexity of the X‐ray images of COVID‐19‐infected patients and the X‐ray images of other types of pneumonia respiratory diseases is well explained by using the fractal dimension. It is also concluded that the fractal dimension discriminates the lung diseases due to COVID‐19 from various pneumonia respiratory diseases.

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

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