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Multifractal based image processing for estimating the complexity of COVID-19 dynamics.

Qiusheng Rong1, C Thangaraj2, D Easwaramoorthy2

  • 1School of Computer and Electrical Engineering, Hunan University of Science and Arts, Changde, 415000 China.

The European Physical Journal. Special Topics
|November 24, 2021
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This study uses Generalized Fractal Dimensions (GFD) to analyze COVID-19 complexity in chest X-rays. The findings help differentiate viral pneumonia from other respiratory diseases using image analysis.

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Area of Science:

  • Medical Imaging
  • Computational Biology
  • Fractal Geometry

Background:

  • COVID-19 poses a global health and economic threat, significantly impacting human lungs.
  • Differentiating COVID-19 from other respiratory diseases using chest X-rays is challenging.
  • Grayscale medical images are crucial for analyzing lung pathologies.

Purpose of the Study:

  • To estimate and analyze the complexity of coronavirus transmission using Generalized Fractal Dimensions (GFD).
  • To evaluate the robustness of COVID-19 detection against noise in chest X-ray images.
  • To compare the complexity of COVID-19 with other respiratory diseases via GFD curves.

Main Methods:

  • Calculation of multifractal dimensions for original, noisy, and denoised grayscale chest X-ray images.
  • Graphical comparison of COVID-19 X-ray images with healthy and other disease images using GFD curves.
  • Evaluation of image denoising performance using Mean Absolute Error (MAE) and Peak Signal-to-Noise Ratio (PSNR).

Main Results:

  • Generalized Fractal Dimensions (GFD) effectively quantify the complexity of lung diseases in chest X-rays.
  • The multifractal analysis demonstrates robustness even with noisy or denoised image data.
  • GFD curves provide a graphical method to distinguish COVID-19 complexity from other respiratory conditions.

Conclusions:

  • GFD is a valuable tool for analyzing and differentiating respiratory diseases, including COVID-19, from chest X-rays.
  • The proposed method offers a robust approach for medical image analysis in pandemic scenarios.
  • This research contributes to improved diagnostic capabilities for lung infections through advanced image processing techniques.