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

Magdalena Jasionowska , Artur Przelaskowski

Abstract

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.
Author Magdalena Jasionowska (FMIS / DCSDCAM)
Magdalena Jasionowska,,
- Department of CAD/CAM Systems Design and Computer-Aided Medicine
, Artur Przelaskowski (FMIS / DCSDCAM)
Artur Przelaskowski,,
- Department of CAD/CAM Systems Design and Computer-Aided Medicine
Journal seriesPattern Analysis and Applications, ISSN 1433-7541, (A 20 pkt)
Issue year2018
Pages1-10
Publication size in sheets0.5
Keywords in EnglishMultiscale transform domains, Angular selectivity, Angular resolution, Mammographic spicules representation
ASJC Classification1702 Artificial Intelligence; 1707 Computer Vision and Pattern Recognition
DOIDOI:10.1007/s10044-018-0698-z
URL https://link.springer.com/article/10.1007/s10044-018-0698-z
Languageen angielski
Score (nominal)20
ScoreMinisterial score = 20.0, 11-07-2019, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.978; WoS Impact Factor: 2017 = 1.281 (2) - 2017=1.267 (5)
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