Texture extraction algorithm based on Wavelet and CLBP for classification of lesions in mammograms

• Yan A. S. Duarte UFABC
• Marcelo Z. do Nascimento UFU
• Domingos L. L. Oliveiras UFABC

Abstract

This article presents a Computer Aided Diagnosis (CAD) system to the classification of mammograms lesions. The ROI’s were obtained from the Digital Database for Screening Mammography (DDSM). The Wavelet Transform was used for generation of images in space and frequency domain. After that, the Completed Local Binary Pattern (CLBP) operator was applied to the textural features extraction. Redundant attributes were eliminated with the technique of variance analysis (ANOVA). Finally, the cases were classified with the artificial neural network of Radial Basis Function (RBF). Quantitative analysis by area under ROC curve reached 100% of effectiveness with the proposed method.

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