A hierarchical classification method for mammographic lesions using wavelet transform and spatial features

Authors:
Silvana G. Dellepiane;Irene Minetti;Sara Dellepiane
Affiliations:
University of Genoa, Dept. of Biophysical and Electronic Engineering, Genova, Italy;University of Genoa, Dept. of Biophysical and Electronic Engineering, Genova, Italy;University of Genoa, Dept. of Biophysical and Electronic Engineering, Genova, Italy
Venue:
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
Year:
2010

Citing 2
Cited 0

Analysis of mammogram classification using a wavelet transform decomposition

Pattern Recognition Letters - Special issue: Sibgrapi 2001
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

A supervised hierarchical classification for mammographic images is here presented, based on the analysis of wavelet transform. The proposed method analyses different wavelet transform decomposition levels at the same time and innovatively treats them as new images taking into account also their spatial, contextual and morphological properties. The proposed method is very simple and transparent to the user, but it is able to achieve very good classification results. Since it is very fast, we foresee its future application not only for classification purposes, but also for pathology automatic localization. MIAS database has been used in order to compare results with the ones presented in literature.