Fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m. Fractal Analysis of Breast Masses in Mammograms 2019-03-24

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Breast Cancer Prognosis and Treatment

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

The long term objective of the research is to link the microscopic features of granular media with the mechanical behaviour observed in the laboratory and in situ. Further, improvement in tracking performance was slightly less than the square-root of the reduction in noise, approximately 84-90%. We propose a detection and classification system for the analysis of mammographic calcifications. Computer techniques proposed to date for tumor analysis have concentrated on shape factors of tumor regions and texture measures. Contents: Preface -- Acknowledgments -- List of symbols and abbreviations. In computerised shape analysis, it is desirable to classify objects using robust features, which are independent of scaling, translation, and rotation, and possibly not affected by roughness coming from noise.

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Fractal Analysis of Breast Masses in Mammograms: Thanh M. Cabral: 9781627050692: Telegraph bookshop

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

Lung cancer is one of the deadliest cancers in both men and women. However, 81% of this reduction is appreciated between 290 and 1000 μm. The analysis is performed after injecting 11 patients with a contrast agent and 16 mass lesions were extracted from these patients. In applications, where large number of images is involved, the computation cost is very high. Previous studies have shown that percolation-like scaling generally inhibits transport. Thus, the novel techniques proposed herein offer satisfactory tumor identification.

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Fractal Analysis of Breast Masses in Mammograms av Thanh M. Cabral (Heftet)

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

The objective of this work is to test the effectiveness of combined use of local and global features in detecting abnormalities in mammograms. Buying eBooks from abroad For tax law reasons we can sell eBooks just within Germany and Switzerland. Further, neither measure was strongly dependent on simulated changes in mammographic technique. The results indicate the importance of including lesion edge definition with shape information for classification of tumors, and that the proposed measure of acutance fills this need. Moreover, our algorithm captured the knowledge of expert dermatologists in analysing malignancy of a lesion based on its shape alone, indicating that the new measures may be useful for diagnosing melanomas. This article is protected by copyright.

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Fractal analysis of breast masses in mammograms (eBook, 2012) [roomdeal.in]

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

Description: 1 online resource xx, 98 pages : illustrations. Summary Fractal analysis is useful in digital image processing for the characterization of shape roughness and gray-scale texture or complexity. We present a study of four methods to compute the fractal dimension of the contours of breast masses, including the ruler method and the box counting method applied to 1D and 2D representations of the contours. The combination of all the three features achieved 91% accuracy of circumscribed versus spiculated classification of masses based on shape. One of the commonly missed signs of breast cancer is architectural distortion. An efficient implementation of the Peanoscanning operation based on the symmetry exhibited by the Peano-Hilbert curve is also suggested.

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Fractal Analysis of Contours of Breast Masses in Mammograms

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

An analysis of the dependence of the performance of classifier using fractal based texture analysis, on the number of decomposed binary images, has been discussed. © 2001 American Association of Physicists in Medicine. Both descriptors are brie y reviewed and some preliminary results of their application to the morphometric characterization of neural cells are presented. First, a new multi-tolerance region growing method is proposed for the detection of potential calcification regions and extraction of their contours. The main goals are: 1 the identification of bilateral asymmetry as an early sign of breast disease which is not detectable by other existing approaches; and 2 the detection and classification of masses and regions of architectural distortion, as benign lesions or malignant tumors, in a unified framework that does not require accurate extraction of the contours of the lesions. In this reported work fractal geometry has been used for both skin lesion border irregularity measurement and texture features extraction.

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Fractal analysis of breast masses in mammograms

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

The outcome of each case was determined. Single reading of one view results in a low detection rate of small invasive cancers for most individual programmes. The purpose of the present study is to provide a recent update on the status of this rapidly emerging field by performing a systematic review of the literature on radiomics, with a primary focus on oncologic applications. A novel algorithm to compute the super-pixels has also been proposed to detect the damaged cup. We applied a box-counting algorithm to determine the fractal dimension of atypical nuclei in dysplastic cervical epithelium. When the leave-one-case-out method was applied to partition the data set into trainers and testers, the average test Az for the task of classifying the mass on a single mammographic view was 0. The method is based on the calculation of the 'fractal dimension' of digitised mammograms.

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Fractal Analysis of Breast Masses in Mammograms

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

The result is an algorithm for reliably estimating the fractal dimension of surfaces or, more generally, graphs of functions of several variables. Results: To classify the samples, a new architecture for combination of the classifiers is proposed. One highly promising approach appears to be a combination of fractal analysis, that provides a quantitative description of shapes, with radiographic images able to discriminate malignant from benign tumor masses, and also from normal tissue structures. In the second stage, an ensembled fully complex-valued relaxation network classifier is used for classifying mammograms. To estimate and compare the accuracy of diagnostic tests for the detection of any skin cancer or skin lesion with a high risk of progression to melanoma.

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Fractal analysis of breast masses in mammograms (eBook, 2012) [roomdeal.in]

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

Dermoscopy, a non-invasive imaging technique has been significantly used by the doctors and radiologists for the early diagnosis of the various skin disorders. The shape features described include compactness, spiculation index, fractional concavity, and Fourier factor. It is a ratio providing a statistical index of complexity comparing how detail in a fractal pattern changes with the scale at which it is measured. System requirements: Adobe Acrobat Reader. It is now well established that the majority of tumours is characterized by a high glucose consumption, even under aerobic conditions, in absence of the Pasteur Effect, i. Mobile agents can move between data sources such as the atlas and hospital repositories, perform computational tasks at each site, and return only relevant data to the user. Normally, a breast tumor is identified as benign or malignant through biopsy.

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Fractal Analysis of Breast Masses in Mammograms

fractal analysis of breast masses in mammograms rangayyan rangaraj cabral thanh m

Fractal geometry is a tool used to characterize irregularly shaped and complex figures. Out of the total images used for evaluation 74 images were malignant and other 74 images were benign. The value of mucinous cystadenoma of low malignant potential was 1. Best results pertain to an accuracy of 92. Growing tumors show vascular networks that progressively deviate from their normal pattern, in which they seem to follow diffusion-limited aggregation to a pathological condition in which they display scaling similar to percolation clusters near the percolation threshold. These include measures of the skewness of the image brightness histogram, and of image texture characterized by the fractal dimension.

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