Abstract:The current prognostic parameters, including tumor volume, biochemistry, or immunohistochemistry, are not sufficient to reflect the properties of cancer cells that distinguish them from normal cells. Our focus is to evaluate the effects of a combination of microtubule-polymerizing Taxol and -depolymerizing colchicine on IAR20 PC1 liver cells by measuring the surface fractal dimension as a descriptor of two-dimensional vascular geometrical complexity. The fractal dimension offers a rapid means of assessing cell… Show more
“…can be characterized by fractal analysis by using two statistical measures known as the fractal dimension ( D F ) and lacunarity ( λ ). Image analysis that employs the use of fractals has been used in many areas (Jelinek & Fernandez, 1998; Yaşar & Akgünlü, 2005; Al-Kadi & Watson, 2008; Updike & Nowzari, 2008; Uppal et al, 2010; Karperien et al, 2013), including image segmentation (Dubuisson & Dubes, 1994; Keller et al, 1989) and the classification of ecological (Kenkel & Walker, 1993; Malhi & Román-Cuesta, 2008) and urban (Myint & Lam, 2005) spatial distributions.Figure 1 a: Koch snowflake. b: Schematic demonstrating the gliding box-counting algorithm for the lacunarity analysis of a binary image of size M .…”
Biomimetic hierarchical surface structures that exhibit features having multiple length scales have been used in many technological and engineering applications. Their surface topographies are most commonly analyzed using scanning electron microscopy (SEM), which only allows for qualitative visual assessments. Here we introduce fractal and lacunarity analyses as a method of characterizing the SEM images of hierarchical surface structures in a quantitative manner. Taking femtosecond laser-irradiated metals as an example, our results illustrate that, while the fractal dimension is a poor descriptor of surface complexity, lacunarity analysis can successfully quantify the spatial texture of an SEM image; this, in turn, provides a convenient means of reporting changes in surface topography with respect to changes in processing parameters. Furthermore, lacunarity plots are shown to be sensitive to the different length scales present within a hierarchical structure due to the reversal of lacunarity trends at specific magnifications where new features become resolvable. Finally, we have established a consistent method of detecting pattern sizes in an image from the oscillation of lacunarity plots. Therefore, we promote the adoption of lacunarity analysis as a powerful tool for quantitative characterization of, but not limited to, multi-scale hierarchical surface topographies.
“…can be characterized by fractal analysis by using two statistical measures known as the fractal dimension ( D F ) and lacunarity ( λ ). Image analysis that employs the use of fractals has been used in many areas (Jelinek & Fernandez, 1998; Yaşar & Akgünlü, 2005; Al-Kadi & Watson, 2008; Updike & Nowzari, 2008; Uppal et al, 2010; Karperien et al, 2013), including image segmentation (Dubuisson & Dubes, 1994; Keller et al, 1989) and the classification of ecological (Kenkel & Walker, 1993; Malhi & Román-Cuesta, 2008) and urban (Myint & Lam, 2005) spatial distributions.Figure 1 a: Koch snowflake. b: Schematic demonstrating the gliding box-counting algorithm for the lacunarity analysis of a binary image of size M .…”
Biomimetic hierarchical surface structures that exhibit features having multiple length scales have been used in many technological and engineering applications. Their surface topographies are most commonly analyzed using scanning electron microscopy (SEM), which only allows for qualitative visual assessments. Here we introduce fractal and lacunarity analyses as a method of characterizing the SEM images of hierarchical surface structures in a quantitative manner. Taking femtosecond laser-irradiated metals as an example, our results illustrate that, while the fractal dimension is a poor descriptor of surface complexity, lacunarity analysis can successfully quantify the spatial texture of an SEM image; this, in turn, provides a convenient means of reporting changes in surface topography with respect to changes in processing parameters. Furthermore, lacunarity plots are shown to be sensitive to the different length scales present within a hierarchical structure due to the reversal of lacunarity trends at specific magnifications where new features become resolvable. Finally, we have established a consistent method of detecting pattern sizes in an image from the oscillation of lacunarity plots. Therefore, we promote the adoption of lacunarity analysis as a powerful tool for quantitative characterization of, but not limited to, multi-scale hierarchical surface topographies.
“…He reported that FD values are significantly different for each TNM stage, thus validating the method as a tool for cancer stadialization (19). Uppal et al showed the correlations of fractal dimensions of cell contours with the latent factors (20).…”
Section: Discussionmentioning
confidence: 98%
“…Fractal analysis measures the complexity of geometric structures. The fractal dimension offers a rapid means of assessing cell shape analysis (16). Many analytical methods have been proposed to determine the fractal dimension of natural objects.…”
Our aim is to investigate the detection of fractal dimension (Box-counting dimensions) with protective effects of lycopene and catechin in carbon tetrachloride-treated rat's liver. Fractal dimension measure intensity and complexity of subject. The rats were divided into six groups as liquid oil, lycopene, catechin, carbon tetrachloride plus lycopene, carbon tetrachloride plus catechin and carbon tetrachloride. The tissue samples were obtained at end of 2İst day. The liver tissue distortions were evaluated using hematoxylin and eosin staining. The regions of hepatocyte were separated into Small Square under light microscopy. Then, counted at least one nucleus with intersection of one square. Fractal dimension were determined by using this formula; ln(N(n))/ln(2 n ). Notably, there was no difference between control and catechin-treated rats on fractal dimension values. But, a lycopene value was bigger than control and catechin administrated rats. In carbon tetrachloride-treated rat, fractal dimension is less. It was increased in lycopene plus carbon tetrachloride and catechin plus carbon tetrachloride with compare to carbon tetrachloride group. The findings confirmed, if hepatocyte is less, fractal dimension will decrease On other hand, carbon tetrachloride decreased fractal dimension due to less hepatocyte. It was increased in fractal dimension due to high hepatocyte in catechin and lycopene treated rats, because of their protective effects. This study is combination of medicine and mathematics, as fractal dimension. It was calculated, toxicity and protective effects of antioxidant materials could be determined in this way. KEY WORDS: CCl4, Lycopene, catechin, Fractal dimension ÖZET: Amacımız karbon tetraklorür uygulanmış sıçan karaciğerinde likopen ve kateşinin koruyucu etkilerinin fraktal boyut hesaplaması kullanılarak ortaya konmasıdır. Fraktal boyut nesnenin yoğunluğunu ve karmaşıklığını ölçer. Sıçanlar; sıvı yağ, likopen, kateşin, karbon tetraklorür + likopen, karbon tetraklorür + kateşin ve karbon tetraklorür olmak üzere altı gruba ayrıldı. Doku örnekleri 21. gün sonunda elde edildi. Karaciğer dokusundaki harabiyet, hematoksilen ve eozin boyama ile değerlendirildi. Hepatosit bölgeleri ışık mikroskobu altında küçük karelere ayrıldı. Sonra en az bir nükleusun bir kareyle kesiştiği alan sayıldı. Fraktal boyut ln(N(n))/ln(2 n ) formülle hesaplandı. Özellikle, fraktal boyut değerleri açısından kontrol ve kateşin ile tedavi edilen gruplar arasında bir fark yoktu. Ama likopen değerleri kontrol ve kateşin uygulanan sıçanlarda daha yüksek bulundu. Karbon tetraklorür uygulanmış sıçanlarda fraktal boyut düşüktü. Karbon tetraklorür uygulanmış gruba göre karbon tetraklorür + likopen ve karbon tetraklorür + kateşin gruplarında fraktal boyutta artış gözlendi. Bulgular hepatosit miktarındaki azalmaın, fraktal boyutun azalmaya neden olacağını göstermiştir. Diğer taraftan, karbon tetraklorür hepatositlerin az olması nedeniyle fraktal boyutu azaltmıştır. Kateşin ve likopen uygulanan gruplarda yüksek hepatosit miktar...
“…However, our study showed that these changes, though not so obvious, occur much early during cell structural reorganization induced by UV light exposure. It is known that cell surface roughness and shape have a substantial impact on cell fractal characteristics and cytoplasm FD is particularly known to be influenced not only by heterogeneity of the image, but also by irregularities detected on an object’s surface (Uppal et al, 2010; Wang et al, 2010; Dokukin et al, 2011). Unlike lacunarity, which is firmly related to the gappiness of image texture, FD values are more likely to be influenced by border pixels of the image ROI.…”
The aim of this study is to determine the ability and consequent significance of fractal and lacunarity analysis together with computational morphometric and gray-level co-occurrence matrix (GLCM) analysis in detecting subtle initial UVB-induced chromatin and cytosolic changes in neutrophil granulocytes. In addition, the direction and potential significance of the observed changes is speculated. Feulgen-stained neutrophils are pictured and their digitalized images are analyzed in specialized software for digital image processing and ImageJ analysis. Significant statistical difference is observed (p0.05). For other parameters there was mostly high statistical significance (p>0.05). Significant unmatched correlations were found as sensitive markers of early morphological changes in cells exposed to UV light. In addition, the correlation between nuclear area and entropy was determined and was highly significant (p<0.001). UVB light, due to its high absorbance by DNA molecules, leads to double behavior of the cells. On one hand, cells start to rearrange but on the other UV light starts very early to immediately damage the cell. All these processes are very subtle in their intensity and GLCM analysis and computational imaging methods based on fractal geometry, i.e. fractal and morphometric analysis, in particular their combination, are very sensitive for detecting and describing these early chromatin changes.
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