ArticleThe European physical journal. Special topics2021
Multifractal based image processing for estimating the complexity of COVID-19 dynamics.
Article in The European physical journal. Special topics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed, 10 citations in OpenAlex.
- Ten quick tips for computational analysis of medical images.PLoS computational biology · 2023Article
- Frontiers of fractals for complex systems: recent advances and future challenges.The European physical journal. Special topics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic creates a worldwide threat to human health, medical practitioners, social structures, and finance sectors. The coronavirus epidemic has a significant impact on people's health, survival, employment, and financial crises; while also having noticeable harmful effects on our environment in a short span of time. In this context, the complexity of the Corona Virus transmission is estimated and analyzed by the measure of non-linearity called the Generalized Fractal Dimensions (GFD) on the chest X-Ray images. Grayscale image is considered as the most important suitable tool in the medical image processing. Particularly, COVID-19 affects the human lungs vigorously within a few days. It is a very challenging task to differentiate the COVID-19 infections from the various respiratory diseases represented in this study. The multifractal dimension measure is calculated for the original, noisy and denoised images to estimate the robustness of COVID-19 and other noticeable diseases. Also the comparison of COVID-19 X-Ray images is performed graphically with the images of healthy and other diseases to state the level of complexity of diseases in terms of GFD curves. In addition, the Mean Absolute Error (MAE) and the Peak Signal-to-Noise Ratio (PSNR) are used to evaluate the performance of the denoising process involved in the proposed comparative analysis of the representative grayscale images.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.