Fractal dimension and image statistics of anal intraepithelial neoplasia (original) (raw)
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Fractal Analysis of Cervical Intraepithelial Neoplasia
Introduction: Cervical intraepithelial neoplasias (CIN) represent precursor lesions of cervical cancer. These neoplastic lesions are traditionally subdivided into three categories CIN 1, CIN 2, and CIN 3, using microscopical criteria. The relation between grades of cervical intraepithelial neoplasia (CIN) and its fractal dimension was investigated to establish a basis for an objective diagnosis using the method proposed.
Image statistics and data mining of anal intraepithelial neoplasia
Pattern Recognition Letters, 2008
Anal intraepithelial neoplasia (AIN) is a precancerous condition of growing concern, due to the strong interrelation of AIN with infections caused by human papillomaviruses (HPV) and HIV. Several HPV-subtypes induce a variety of tumorous skin lesions and cause different stages of dysplasia and even cancer. The histological classification of AIN is becoming more and more important in clinical practice, due to increasing HPV infection rates throughout human population. Histological slices of anal tissues are commonly classified by individual inspections with all the unavoidable differences of the training status and variances of the individual.
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We propose new method of assessment of histological images for medical diagnostics. 2-D image is preprocessed to form 1-D landscapes or 1-D signature of the image contour and then their complexity is analyzed using Higuchi's fractal dimension method. The method may have broad medical application, from choosing implant materials to differentiation between benign masses and malignant breast tumors.
The aplication of the fractal analysis in oncopathology
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Fractal analysis is an objective approach that in oncopathology is one of the important fields of application. In this study is present fractal methodologies at histological level that have been successfully applied to characterize pathological features and able to perform differential diagnosis and prognosis in oncopathology. The basic principles and prospects of fractal geometry in pathology are promising. In particular, fractal analysis is emerging as a powerful tool to perform differential diagnosis and prognosis of the patients in cancer and other malignancies as well to improve the effectiveness and safety of patient care. All fractal objects have Fractal Dimension FDs, commonly calculated with box counting. Morphometry, the measure of shapes of the structures, can be added to every imaging technique in order to obtain objective indexes. In this field, fractal analysis has been applied to histopathology, cytopathology, and electron microscopy with great success. Performing fra...
Journal of Biosciences and Medicines, 2018
Background: The concomitant use of fractal and Euclidian measurements has led to the development of new methodologies of cell evaluation, including a diagnosis of cervical cells that set up differences between normality and various degrees of lesion, to carcinoma. Aim: To confirm the diagnostic capacity of the methodology based on fractal and Euclidian geometry for the mathematical diagnosis through a blind study of normal cells and with different types of lesion, as atypia of undetermined significance (ASCUS), low grade squamous intra-epithelial lesion (LGSIL) and high grade squamous intra-epithelial lesion (HGSIL). Methods: 100 cells of Papanicolaou tests were analyzed and divided into 4 groups according to conventional parameters: 25 normal, 25 ASCUS, 25 LGSIL and 25 HGSIL. By means of the Box-counting Fractal Space, we calculated the fractal dimension and occupying spaces of the border and surface in pixels of the cell nucleus and cytoplasm. The diagnostic parameters of the previously developed methodology were applied and compared with the conventional diagnosis, setting up sensibility, specificity, negative likelihood ratio and Kappa coefficient. Results: The values of the occupation of the border and surface of the cell nucleus and cytoplasm were consistent with the values found by the diagnostic methodology previously found. The subtraction of the nucleus and cytoplasm frontiers presented values between: 189 and 482 for normality; 159
Fractal analysis in the detection of colonic cancer images
IEEE Transactions on Information Technology in Biomedicine, 2002
The aim of this study was to investigate the value of fractal dimension in separating normal and cancerous images, and to examine the relationship between fractal dimension and traditional texture analysis features. Forty-four normal images and 58 cancer images from sections of the colon were analyzed. A "leave-one-out" analysis approach was used to classify the samples into each group. With fractal analysis there was a highly significant difference between groups ( 0 0001). Correlation and entropy features showed greater differences between the groups ( 0 0001). Nevertheless, the addition of fractal analysis to the feature analysis improved the sensitivity from 90% to 95% and specificity from 86% to 93%.
Journal of Medical Science And clinical Research
Introduction: The entire continuum of Oral potentially malignant-malignant disorders is dogged with numerous uncertainties during their diagnosis. Particularly affected by these indecisions and predicaments are verrucous hyperplasia, verrucous carcinoma and squamous cell carcinoma. Substantial and objective studies are required in order to better define the biologic behavior and prognosis of these lesions and to distinguish closely resembling lesions from one another. Aim: To evaluate and compare nuclear fractal dimensions (nFD) & fractal dimensions of epithelial connective tissue interface (eFD) for-Leukoplakia histopathologically diagnosed as Oral Epithelial Dysplasia (OED), Oral Verrucous Carcinoma (VC) and Oral Squamous Cell Carcinoma (OSCC). Materials & Method: 60 archived paraffin embedded tissue sections stained with H&E which were segregated into 3 groups-OED (20), VC (20), OSCC (20). Five fields each at low power (10x) and high power (40x) were captured for each section using Magnus Image-Pro System. Histo-morphometric analysis of nucleus and ECTI was carried out with the help of Computer aided image analysis software-Image ProPremier 9.1.
2017
Medical images typically have irregular and fragmented contours. This is a strong motivation to use fractal geometry, rather than Euclidian geometry, for their description and characterization. In this paper we analyse a set of 100 images of melanoma and non-melanoma moles. The moles have their contours extracted with several tools and then the contours have their fractal dimension computed with distinct estimators. We have used descriptive statistics to depict that the fractal dimension does not give clear classification or systematization of the moles. We have also applied the student’s t-test to show that in the considered cases the two sets of fractal dimensions of melanoma and non-melanoma moles are not statistically different.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
it is known that the malignancy of breast lesions is strongly correlated with their shape; the more irregular the lesion is, the more malignant it tends to be. For this reason, CAD systems aimed at assisting the classification of breast lesions often rely on quantitative measures, such as fractal dimension (FD), which can help characterizing the smoothness (or the roughness) of the lesion's shape (1).