Characteristics of Architectural Distortions in Mammograms - Extraction of Texture Orientation with Gabor Filters

Jasionowska, Magdalena; Przelaskowski, Artur; Jóźwiak, Rafał

doi:10.1007/978-3-642-15910-7_48

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…Considering those properties, the bases or frames of tensor wavelets, complex wavelets, contourlets and curvelets were selected to be experimentally verified, based on a spicule phantom model which contains object (line) value of 1 and slightly Gaussian blurred lines of approx. 9-pixel in width and 90-pixel in length which are estimated averaged sizes of spicules according to our previous study [13]. The angle range of line distribution was assumed as: 0 • -360 • and different center size of line convergence was adopted: the sparse phantom ( Fig.…”

Section: Spicule Phantom Modelmentioning

confidence: 99%

“…tion step, whereas the pkva filter was used for the directional decomposition step [16]; • complex-valued curvelet transform [7] for four scales, including the coarsest wavelet level, and three directional scales, where the coarsest scale was divided into eight angular ranges [7]; • complex wavelet transform with six levels of decomposition, near-symmetric (13,19)-tap filters as biorthogonal filters and Q-Shift orthogonal (10,10)-tap filters [10,11]; six complex highpass subimages for each of all levels were generated as the result of the transformation.…”

Section: Directional Activity Of Multiscale Wavelet-like Domainsmentioning

confidence: 99%

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Wavelet-like selective representations of multidirectional structures: a mammography case

Jasionowska

Przelaskowski

2018

Pattern Anal Applic

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The subject of this paper is selective representation of informative texture directionality in sparse domain of four verified multiscale transforms: contourlets, curvelets, tensor and complex wavelets. Directionality of linear or piecewise linear structures is a fundamental property in recognition of anatomical structures, i.e. separating the brain regions, directional characteristics of small coronary arteries. Another important example is spicule extraction in mammograms which is based on directional analysis of malignant spiculated lesions. The originality of the proposed experiments lies in optimization of multiscale wavelet-like representations to differentiate multidirectional structures of architectural distortions and spiculated masses in low-contrast noisy mammograms. For that purpose, the applied method consists in proposed phantom-based normalization and defined assessment criteria of directional information activity. The directional activity including both measures of angular resolution and angular selectivity was determined relative to increased background density and noise simulating reduced perceptibility of the analyzed objects. A numerically modeled phantom of multidirectional linear structures was used to assess subjectively and objectively the efficiency of nonlinear approximation for radially diverging spicule-like structures. Size and distribution of the structures simulates essential nature of spiculated signs of breast cancer. Basing on the experimental results, the complex wavelet domain was concluded to be the most effective tool to uniquely represent relevant information in the form of multidirectional piecewise linear structures in low-contrast noisy mammograms.

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Section: Spicule Phantom Modelmentioning

confidence: 99%

Section: Directional Activity Of Multiscale Wavelet-like Domainsmentioning

confidence: 99%

Wavelet-like selective representations of multidirectional structures: a mammography case

Jasionowska

Przelaskowski

2018

Pattern Anal Applic

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“…The amplitude of magnitude images were compared at each pixel and the maximum amplitude are detected. The angle at which the maximum amplitude occur the corresponding value of the Phase image is stored as the dominant image [17].…”

Section: Estimation Of Dominant Anglementioning

confidence: 99%

Architectural Distortion Detection in Mammogram using Contourlet Transform and Texture Features

Anand¹,

Rathna²

2013

IJCA

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Breast Cancer is one of the most affecting diseases in the world. Architectural Distortion is one of the indications of breast cancer. It is an abnormal arrangement of tissue strands of the breast, often a radial or perhaps a somewhat random pattern, but without any associated mass as the apparent cause of this distortion. This project used Contourlet Transform based method to detect the location of the architectural distortion in mammograms. The dominant angle is detected in this Contourlet decomposition which comprises of Laplacian Pyramidal Filter bank and Steerable Gaussian Filter. The textural features will not show any deviation in the distorted area. Here the methods proposed will assist the Radiologist to identify the unidentified potential sites of distortion. Therefore the main aim of this work becomes the reduction of the region of interests. In this project 39 cases were testes in which 19 are Architectural Distorted image from the MIAS database and 17 Normal images. The proposed algorithm detected 1502 regions of interest (ROIs) with 247 True Positives and 1255 False Positives. In this paper 26 textural features were considered and result is obtained as 0.77 with an artificial neural network. The proposed methods have significant result in detecting the architectural distortion in mammograms of interval cancer cases.

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Angular Resolution Study of Vectors Representing Subtle Spiculated Structures in Mammograms

Jasionowska

Przelaskowski

2014

Advances in Intelligent Systems and Computing

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Characteristics of Architectural Distortions in Mammograms - Extraction of Texture Orientation with Gabor Filters

Cited by 5 publications

References 3 publications

Wavelet-like selective representations of multidirectional structures: a mammography case

Wavelet-like selective representations of multidirectional structures: a mammography case

Architectural Distortion Detection in Mammogram using Contourlet Transform and Texture Features

Angular Resolution Study of Vectors Representing Subtle Spiculated Structures in Mammograms

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