2012
DOI: 10.1016/j.proeng.2012.01.1262
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Texture Analysis of Breast Cancer Cells in Microscopic Images Using Critical Exponent Analysis Method

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Cited by 12 publications
(6 citation statements)
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“…Bauer and Mackenzie [ 10 ] found that none of the cells of the healthy patients had a D f larger than 1.28, while a large percentage of the cancer patients cells had D f >1.28. Phinyomark et al [ 8 ] found that for self‐affine surfaces with a D f <2, the surfaces are similar to the histological structures of breast cancer with a D f of 1.66. The topography of porous polystyrene is similar to the histological structures, such as cancer cells topography, and the D f agrees with those reported in the literature for cancerous structures, which suggests that is possible for the use of AFM topographies of polystyrene films with different degrees of porosity to be used as patterns in digital recognition techniques to detect cancer.…”
Section: Resultsmentioning
confidence: 99%
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“…Bauer and Mackenzie [ 10 ] found that none of the cells of the healthy patients had a D f larger than 1.28, while a large percentage of the cancer patients cells had D f >1.28. Phinyomark et al [ 8 ] found that for self‐affine surfaces with a D f <2, the surfaces are similar to the histological structures of breast cancer with a D f of 1.66. The topography of porous polystyrene is similar to the histological structures, such as cancer cells topography, and the D f agrees with those reported in the literature for cancerous structures, which suggests that is possible for the use of AFM topographies of polystyrene films with different degrees of porosity to be used as patterns in digital recognition techniques to detect cancer.…”
Section: Resultsmentioning
confidence: 99%
“…Today, modern neurosciences admit the prevalence of fractal properties in the brain at various levels of observation, from the micro‐scale to the macro‐scale, in the molecular, anatomical, functional, and pathological perspectives. Phinyomark et al [ 8 ] explored the application of fractal analysis to study the textural characteristics of microscopic images, using the critical expression analysis method to improve the ability to classify microscopic images of histologic structures from breast cancer with a complex structure. The work presented by Di Leva et al, [ 9 ] shows a holistic view of the fractal geometry of the brain and reviews the basic concepts of fractal analysis and its main applications to basic neurosciences.…”
Section: Introductionmentioning
confidence: 99%
“…We applied the similar idea to classify BCMI into three categories, i.e. SC, LC, and cancer cells based on the FD value determined using critical exponent analysis method (Phinyomark et al ., ). However, the orientation of stromal, lymphocyte, and cancer cells causes the different FD values when they were determined using horizontal and vertical landscape signals.…”
Section: Introductionmentioning
confidence: 97%
“…Because of its geometrical complexity and irregularity, the quanti cation of tumour morphology is approached by computational analysis and increasing involvement of arti cial intelligence 5,6 . The morphology characteristics that cannot be quanti ed visually have been commonly analysed by mathematical tools such as the fractal analysis and grey level co-occurrence matrix (GLCM) 7,8 . For instance, the fractal dimension numerically quanti es the disorder or complexity of an object, with low values indicating regular structures and high values corresponding to more irregular structures with randomness.…”
Section: Introductionmentioning
confidence: 99%