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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Slovenian Society for Stereology and Quantitative Image Analysis
2011-05-01
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Online Access: | http://www.ias-iss.org/ojs/IAS/article/view/674 |
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doaj-72858a529e7f499d9251afb46aa7c5e12020-11-25T02:27:14ZengSlovenian Society for Stereology and Quantitative Image AnalysisImage Analysis and Stereology1580-31391854-51652011-05-0120316917410.5566/ias.v20.p169-174646WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMSPierre KestenerJean Marc LinaPhilippe Saint-JeanAlain ArneodoWe 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.http://www.ias-iss.org/ojs/IAS/article/view/674breast tissuefractional Brownian motionsHurst exponentimage analysismammogrammicrocalcificationsmultifractal formalismrough surfacescale invariancewavelet transform |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pierre Kestener Jean Marc Lina Philippe Saint-Jean Alain Arneodo |
spellingShingle |
Pierre Kestener Jean Marc Lina Philippe Saint-Jean Alain Arneodo WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS Image Analysis and Stereology breast tissue fractional Brownian motions Hurst exponent image analysis mammogram microcalcifications multifractal formalism rough surface scale invariance wavelet transform |
author_facet |
Pierre Kestener Jean Marc Lina Philippe Saint-Jean Alain Arneodo |
author_sort |
Pierre Kestener |
title |
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS |
title_short |
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS |
title_full |
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS |
title_fullStr |
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS |
title_full_unstemmed |
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS |
title_sort |
wavelet-based multifractal formalism to assist in diagnosis in digitized mammograms |
publisher |
Slovenian Society for Stereology and Quantitative Image Analysis |
series |
Image Analysis and Stereology |
issn |
1580-3139 1854-5165 |
publishDate |
2011-05-01 |
description |
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. |
topic |
breast tissue fractional Brownian motions Hurst exponent image analysis mammogram microcalcifications multifractal formalism rough surface scale invariance wavelet transform |
url |
http://www.ias-iss.org/ojs/IAS/article/view/674 |
work_keys_str_mv |
AT pierrekestener waveletbasedmultifractalformalismtoassistindiagnosisindigitizedmammograms AT jeanmarclina waveletbasedmultifractalformalismtoassistindiagnosisindigitizedmammograms AT philippesaintjean waveletbasedmultifractalformalismtoassistindiagnosisindigitizedmammograms AT alainarneodo waveletbasedmultifractalformalismtoassistindiagnosisindigitizedmammograms |
_version_ |
1724843446518153216 |