WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS

WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS

We apply the 2D wavelet transform (WTMM) method to perform a multifractal analysis of digitized mammograms. We show that normal regions display monofractal scaling properties as characterized by the socalled Hurst exponent H =0.3±0.1 in fatty areas which look like antipersistent self-similar random...

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Bibliographic Details
Main Authors: Pierre Kestener, Jean Marc Lina, Philippe Saint-Jean, Alain Arneodo
Format: Article
Language:English
Published: Slovenian Society for Stereology and Quantitative Image Analysis 2011-05-01
Series:Image Analysis and Stereology
Subjects:
breast tissue
fractional Brownian motions
Hurst exponent
image analysis
mammogram
microcalcifications
multifractal formalism
rough surface
scale invariance
wavelet transform
Online Access:http://www.ias-iss.org/ojs/IAS/article/view/674
Description
Summary:We apply the 2D wavelet transform (WTMM) method to perform a multifractal analysis of digitized mammograms. We show that normal regions display monofractal scaling properties as characterized by the socalled Hurst exponent H =0.3±0.1 in fatty areas which look like antipersistent self-similar random surfaces, while H=0.65±0.1 in dense areas which exibit long-range correlations and possibly multifractal scaling properties. We further demonstrate that the 2D WTMM method provides a very efficient way to detect tumors as well as microcalcifications (MC) which correspond to much stronger singularities than those involved in the background tissue roughness fluctuations. These preliminary results indicate that the texture discriminatory power of the 2D WTMM method may lead to significant improvement in computer-assisted diagnosis in digitized mammograms.
ISSN:1580-3139
1854-5165

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