THE ROLE OF D-SUMMABLE INFORMATION DIMENSION IN DIFFERENTIATING COVID-19 DISEASE
Aldo Ramirez-Arellano,
Pilar Ortiz-Vilchis () and
Juan Bory-Reyes ()
Additional contact information
Aldo Ramirez-Arellano: SEPI-UPIICSA, Instituto Politécnico Nacional, Ciudad de México, México
Pilar Ortiz-Vilchis: ��SEPI-ESM, Instituto Politécnico Nacional, Ciudad de México, México
Juan Bory-Reyes: ��SEPI-ESIME-Zacatenco, Instituto Politécnico Nacional, Ciudad de México, México
FRACTALS (fractals), 2021, vol. 29, issue 08, 1-11
Abstract:
The current COVID-19 pandemic mainly affects the upper respiratory tract. People with COVID-19 report a wide range of symptoms, some of which are similar to those of common flu, such as sore throat and rhinorrhea. Additionally, COVID-19 shares many clinical symptoms with severe pneumonia, including fever, fatigue, dry cough, and respiratory distress. Several diagnostic strategies, such as the real-time polymerase chain reaction technique and computed tomography imaging, which are more costly than chest radiography, are employed as diagnostic tools. The purpose of this paper is to describe the role of the d-summable information dimension of X-ray images in differentiating several lesions and lung illnesses better than both fractal and information dimensions. The statistical analysis shows that the d-summable information dimension model better describes the information obtained from the X-ray images. Therefore, it is a more precise measure of complexity than the information and box-counting dimension. The results also show that the X-ray images of COVID-19 pneumonia reveal greater damage than those of tuberculosis, pneumonia, and various lung lesions, where the damage is minor or much focused. Because the d-summable information dimension increases as the image complexity decreases, it could pave the way to formulate a new measure to quantify the lung damage and assist the clinical diagnosis based on the area under the d-summable information model. In addition, the physical meaning of the ν parameter in the d-summable information dimension is given.
Keywords: D-Summable Information Dimension; Fractals; Information Dimension; SARS-Cov-2; X-ray Image (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X21502558
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:29:y:2021:i:08:n:s0218348x21502558
Ordering information: This journal article can be ordered from
DOI: 10.1142/S0218348X21502558
Access Statistics for this article
FRACTALS (fractals) is currently edited by Tara Taylor
More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().