Fractal analysis tools for early assessment of liver inflammation induced by chronic consumption of linseed, palm and sunflower oils

Oprić, Dejan; Stankovich, Anica D.; Nenadović, Aleksandra; Kovačević, Sanjin; Obradović, Danilo; Luka, Silvio R. De; Ostojic, Jelena Nesovic; Milašin, Jelena; Ilić, Aleksandra; Trbovich, Alexander M.

doi:10.1016/j.bspc.2020.101959

Cited by 9 publications

(4 citation statements)

References 76 publications

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“…In recent years, different types of computational image analysis have found their application in life sciences, with the potential to change the future of medicine [ 8 , 9 ]. Fractal analysis, as a method for quantifying the complexity of natural objects, is being increasingly used in biomedical research [ 10 – 13 ], including a few studies in the field of microbiology, focusing on bacteria [ 14 , 15 ], fungi [ 16 ], and Plasmodium [ 17 ]. In addition, particle analysis, a computational biology method for precise cell counting [ 18 ], has been successfully applied in several studies for the counting of parasites, including T .…”

Section: Introductionmentioning

confidence: 99%

Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

et al. 2020

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Toxoplasma gondii is an obligate intracellular parasite infecting up to one third of the human population. The central event in the pathogenesis of toxoplasmosis is the conversion of tachyzoites into encysted bradyzoites. A novel approach to analyze the structure of in vivoderived tissue cysts may be the increasingly used computational image analysis. The objective of this study was to quantify the geometrical complexity of T. gondii cysts by morphological, particle, and fractal analysis, as well as to determine if it is impacted by parasite strain, cyst age, and host type. A total of 31 images of T. gondii brain cysts of four type-2 strains (Me49, and local isolates BGD1, BGD14, and BGD26) was analyzed using ImageJ software. The parameters of interest included diameter, circularity, packing density (PD), fractal dimension (FD), and lacunarity. Although cyst diameter varied widely, its negative correlation with PD was observed. Circularity was remarkably close to 1, indicating a perfectly round shape of the cysts. PD and FD did not vary among cysts of different strains, age, and derived from mice of different genetic background. Conversely, lacunarity, which is a measure of heterogeneity, was significantly lower for BGD1 strain vs. all other strains, and higher for Me49 vs. BGD14 and BGD26, but did not differ among Me49 cysts of different age, or those derived from genetically different mice. The results indicate a highly uniform structure and occupancy of the different T. gondii tissue cysts. This study furthers the use of image analysis in describing the structural complexity of T. gondii cyst morphology, and presents the first application of fractal analysis for this purpose. The presented results show that use of a freely available software is a cost-effective approach to advance automated image scoring for T. gondii cysts.

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Section: Introductionmentioning

confidence: 99%

Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

et al. 2020

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“…Here, a total of 18 grid cell sizes were used to obtain data points for fitting the regression curves to describe the scale-count power law dependence. Specifically, grid cells sized ε ∈ {5, 6,7,8,9,10,12,14,16,18,20,23,27,30,35,40,46, 52} px were used in both the box counting method and the cumulative mass method. Figure 1 shows an example binary image of a nucleus and also illustrates the typical nucleus size and the look of the chromatin texture, covered by grid cells of different sizes, ε.…”

Section: Fractal Analysismentioning

confidence: 99%

“…In the field of medical science, the concept of fractals has been used for both image [1][2][3][4][5][6][12][13][14] and signal [15][16][17][18] analysis. The fractal feature-based image analysis employed so far in gastroenterology has shown promising results in cancer research [19][20][21][22][23] and has helped in the analysis of wireless capsule endoscopy [24] and colonoscopy images [25].…”

Section: Introductionmentioning

confidence: 99%

Fractal Parameters as Independent Biomarkers in the Early Diagnosis of Pediatric Onset Inflammatory Bowel Disease

et al. 2023

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Inflammatory bowel disease (IBD), which encompasses two different phenotypes—Crohn’s disease (CD) and ulcerative colitis (UC)—consists of chronic, relapsing disorders of the gastrointestinal tract. In 20–30% of cases, the disease begins in the pediatric age. There have been just a few studies that used fractals for IBD investigation, but none of them analyzed intestinal cell chromatin. The main aim of this study was to assess whether it is possible to differentiate between the two phenotypes in pediatric patients, or either of the phenotypes versus control, using the fractal dimension and lacunarity of intestinal cell chromatin. We analyzed nuclei from at least seven different intestinal segments from each group. In the majority of colon segments, both the fractal dimension (FD) and the lacunarity significantly differed between the UC group and CD group, and the UC group and control group. In addition, the ileocecal valve and rectum were the only segments in which CD could be differentiated from the controls based on the FD. The potential of the fractal analysis of intestinal cell nuclei to serve as an observer-independent histological tool for ulcerative colitis diagnosis was identified for the first time in this study. Our results pave the way for the development of computer-aided diagnosis systems that will assist the physicians in their clinical practice.

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“…Specifically, in recent years, multifractal analysis has received growing attention in biomedical engineering. For example, it was applied in the analysis of various biophysiological signals, including EEG [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ], ECG [ 11 , 12 , 13 , 14 , 15 ], magnetic resonance images and brainstem volume [ 16 , 17 , 18 ], mammograms [ 19 , 20 ], bone radiographic images [ 21 ], retina digital images [ 22 ], dental implant ultrasonic signal [ 23 ], and liver tissue images [ 24 ], to name few.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal Wavelet Leaders

Lahmiri

Tadj

Gargour

2022

Entropy

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Multifractal behavior in the cepstrum representation of healthy and unhealthy infant cry signals is examined by means of wavelet leaders and compared using the Student t-test. The empirical results show that both expiration and inspiration signals exhibit clear evidence of multifractal properties under healthy and unhealthy conditions. In addition, expiration and inspiration signals exhibit more complexity under healthy conditions than under unhealthy conditions. Furthermore, distributions of multifractal characteristics are different across healthy and unhealthy conditions. Hence, this study improves the understanding of infant crying by providing a complete description of its intrinsic dynamics to better evaluate its health status.

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Fractal analysis tools for early assessment of liver inflammation induced by chronic consumption of linseed, palm and sunflower oils

Cited by 9 publications

References 76 publications

Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

Fractal Parameters as Independent Biomarkers in the Early Diagnosis of Pediatric Onset Inflammatory Bowel Disease

Nonlinear Statistical Analysis of Normal and Pathological Infant Cry Signals in Cepstrum Domain by Multifractal Wavelet Leaders

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