A method for the classification of mammograms using a statistical-based feature extraction
by Nebi Gedik
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 38, No. 1, 2022

Abstract: This paper represents a classification system for mammograms using wave atom transforms and feature selection process with t-test statistics. Mammogram images are transformed to the wave atom coefficients using wave atom transform. Next, a matrix is constructed from the coefficients. The matrix is used as the feature matrix in order to classify mammograms. To achieve the maximum classification accuracy rate, t-test statistics with a dynamic thresholding is additionally carried out. As a classifier, support vector machine is employed in the classification phase. According to the experimental results, the method proposed in this paper provides a successful contribution for the classification of mammographic images.

Online publication date: Tue, 15-Feb-2022

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