Multifractal analysis of chest CT images of patients with the 2019 novel coronavirus disease (COVID-19). (March 2022)
- Record Type:
- Journal Article
- Title:
- Multifractal analysis of chest CT images of patients with the 2019 novel coronavirus disease (COVID-19). (March 2022)
- Main Title:
- Multifractal analysis of chest CT images of patients with the 2019 novel coronavirus disease (COVID-19)
- Authors:
- Astinchap, Bandar
Ghanbaripour, Hamta
Amuzgar, Raziye - Abstract:
- Highlights: A multifractal analysis was performed on CT images of patients with COVID-19. We found a way to early detection and quantitatively assessment of lung infection. The capacity dimension (D0 ) as a new identification factors is introduced. We found patients with the D0 value lower than 1.4 can be healed by treatment. Multifractality of the CT images increased with increasing lung infection. Abstract: The present study was done to evaluate chest computed tomography (CT) images of patients with 2019 novel coronavirus disease (COVID-19) by multifractal technique as a new method to find a way for comparing lung infection quantitatively and identifying progression pattern of the disease. The multifractal spectra extracted from analysis of CT images showed that these spectra were correlated with lung infection amount and disease progression so that, multifractal parameters (αmin, αmax, ∆α, f(αmin ), f(αmax ), ∆f(α), α( q = 0), and f(α) max) were strongly dependent on amount of lung infection. The results demonstrated that multifractality of chest CT images was increased with the increase in lung infection in patients. The interesting and promising result was that capacity dimension (D0 ) as a new diagnostic parameter varied linearly with progression and reduction of lung infection. A critical value was found for D0, according to which patients with D0 lower than 1.4 can be healed by treatment. Therefore, herein, a way was found for quantitative assessment of lungHighlights: A multifractal analysis was performed on CT images of patients with COVID-19. We found a way to early detection and quantitatively assessment of lung infection. The capacity dimension (D0 ) as a new identification factors is introduced. We found patients with the D0 value lower than 1.4 can be healed by treatment. Multifractality of the CT images increased with increasing lung infection. Abstract: The present study was done to evaluate chest computed tomography (CT) images of patients with 2019 novel coronavirus disease (COVID-19) by multifractal technique as a new method to find a way for comparing lung infection quantitatively and identifying progression pattern of the disease. The multifractal spectra extracted from analysis of CT images showed that these spectra were correlated with lung infection amount and disease progression so that, multifractal parameters (αmin, αmax, ∆α, f(αmin ), f(αmax ), ∆f(α), α( q = 0), and f(α) max) were strongly dependent on amount of lung infection. The results demonstrated that multifractality of chest CT images was increased with the increase in lung infection in patients. The interesting and promising result was that capacity dimension (D0 ) as a new diagnostic parameter varied linearly with progression and reduction of lung infection. A critical value was found for D0, according to which patients with D0 lower than 1.4 can be healed by treatment. Therefore, herein, a way was found for quantitative assessment of lung infection of patients with COVID-19 by analyzing chest CT images using the multifractal method. This method can be very effective for physicians in diagnosis and treatment of pneumonia caused by COVID-19 and timely identification of therapeutic effects. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 156(2022)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 156(2022)
- Issue Display:
- Volume 156, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 156
- Issue:
- 2022
- Issue Sort Value:
- 2022-0156-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-03
- Subjects:
- CT images -- Multifractal analysis -- COVID-19 -- Lung infection
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2022.111820 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
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