Image Processing for Analysis of Bio-Liquid Films

Baranov, Maksim; Velichko, Elena; Andryakov, A. A.

doi:10.3103/s1060992x20010026

Cited by 11 publications

(5 citation statements)

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“…Research results also confirm that fractal analysis of macroscopic and microscopic methods can be used to quantitatively assess whey protein-based structures [15]. In addition, fractal analysis and methods of morphological processing of images of protein molecules may indicate their functionality [17]. However, these works are devoted to the formation of fractal structures in liquid solutions of proteins or other biological molecules.…”

Section: Introductionmentioning

confidence: 52%

“…A computer program was created in Python using the OpenCV and PyQt5 libraries, allowing to calculate the fractal dimension of structures in ready-made biomolecular films. The detailed data for the preprocessing of images are presented in [17,18].…”

Section: Box-counting Dimensionmentioning

confidence: 99%

“…One of them can be digital image processing with the identification and calculation of geometric parameters. Previous papers describe the results of determining explicit parameters using digital image processing algorithms [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, the description of structures in protein films using the fractal dimension was chosen in our study as more informative, since, for example, their electrical parameters are related to the scale rather than to the spatial periodicity and symmetry. Numerous publications are concerned with the study of fractal structures formed by both protein molecules in solutions and molecular clusters in thin films [14][15][16][17][18]. Additionally, of great interest are fractal structures formed by various biological molecules in connection with inorganic particles for the needs of biotechnology and bioindustry [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Fractal Structures in Dehydrated Films of Protein Solutions

2021

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The article deals with dendritic structures resulting from self-organization processes in aqueous solutions of albumin proteins. The methods for obtaining the structures and experimental results are presented. It is shown that dendrites are fractal structures that are symmetric under certain conditions of their formation and can have different characteristics depending on the isothermal dehydration of liquid samples. The fractal dimension of the structures in films of the albumin protein solution has been calculated. Dependences of the fractal dimension on the concentrations of salts and protein in the initial solutions and also on the dehydration temperature have been revealed. It has been shown that as the protein concentration in the solution grows, the salt concentration for the initiation of the dendritic structure formation increases. It has been found that the temperature dependences of the fractal dimension of the structures become smoother with increasing protein concentration in solutions. The relationship between geometric characteristics of dendrites and self-organization parameters during drying is discussed.

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Section: Introductionmentioning

confidence: 52%

Section: Box-counting Dimensionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of Fractal Structures in Dehydrated Films of Protein Solutions

2021

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“…For one thing, it is difficult to distinguish diseased lung tissue from surrounding healthy tissue because of this tissue's similarity to its surrounding healthy tissue. As a result, computer systems are unable to distinguish certain sections, such as the lungs, from the rest of the body [46].…”

Section: Disease Progressionmentioning

confidence: 99%

Application of Artificial Intelligence for Rapid Prevention of Epidemic Diseases (COVID-19)

2022

IJHPP

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Background: Epidemic diseases are hazardous in terms of a rapid outbreak. Rapid control of these diseases by finding patients and quarantine and treatment can be the only tool to reduce the number of cases and mortality at the beginning of the outbreak, in the absence of therapy and vaccines. COVID-19 (coronavirus) is a deadly viral disease that causes severe respiratory illness and spreads through the air. Artificial intelligence (AI) technologies have played an essential role in solving complex problems. The use of these technologies in response to the challenges posed by the COVID-19 epidemic can reduce the effects of epidemics in various contexts. Objective: The purpose of this article is to review the applications of artificial intelligence in cases of contagious disease. In this work, COVID-19 disease has been used as an example of dangerous infectious diseases (while the studied methods can be used for all contagious diseases), and a systematic review of the literature on the role of artificial intelligence as COVID-19 has become a comprehensive and critical technology for combating epidemiology, diagnosis, and disease progression. Methods: A complete search of the literature has been done using the databases of PubMed, Scopus, Web of Science, and Google Scholar, and other sources. In this work, the aim is to review articles that the authors believe can be helpful in the prevention of infectious diseases in the event of an outbreak of artificial intelligence in the prevention of more casualties. The first steps needed in a flurry of a disease (including coronavirus) include identifying the primary sufferers and isolating them from the public and examining the illness and how the disease has progressed. In these stages, artificial intelligence can very effectively help the medical community and even the government prevent an epidemic. In this study, the keywords COVID-19, artificial intelligence, and infectious diseases have been used. Results: During our literature search, we came across 73 papers. Researchers analyzed studies examining the diagnostic roles and imaging features of patients with COVID-19. The latter were scanned using CT or ultrasound scans, chest radiographs, or positron emission tomography/computed tomography (PET/CT) scans. Chest x-ray and CT scan are the imaging modalities that are most widely utilized for the diagnosis and management of COVID-19 patients, with chest CT scan being more accurate and sensitive in diagnosing COVID-19 at an early stage. Only a handful of studies have looked into the roles of ultrasonography and PET/CT scans in diagnosing COVID-19 infection. Conclusions: We gathered research from the existing COVID-19 literature that employed artificial intelligence-based methodologies to give insights into various domains of COVID-19 in this systematic review. Our findings indicate critical variables, data formats, and COVID-19 sources to help with clinical research and translation. Findings from this study may also assist in reducing the harm caused by the pandemic in the case of such epidemic diseases in the future.

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