Robust mass classification-based local binary pattern variance and shape descriptors
by Alima Damak Masmoudi; Norhen Gargouri Ben Ayed; Dorra Sellami Masmoudi; Riad Abid
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 8, No. 1/2, 2015

Abstract: In several countries, breast cancer is a serious public health problem. Computer-Aided Detection and Diagnosis (CAD) systems have been used with relative success aiding healthcare professionals. The goal of such approach technique is contribute on the radiologist task aiding in the detection of different types of cancer at an early stage. This paper presents a methodology for masses detection on mammographic images based on the Local Binary Pattern Variance (LBPV) and shape descriptors. Classification of these structures is accomplished through Artificial Neural Network (ANN), which separate them in two groups: masses and non-masses. The performance of macro-calcification detection methods is developed using FARABI database. Performance results are given in terms of receiver operating characteristic.

Online publication date: Sun, 25-Jan-2015

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