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Neural Systems Approach for Ammography Finding by Utilizing Wavelet Features

Journal: International Journal of Science and Research (IJSR) (Vol.3, No. 11)

Publication Date:

Authors : ; ;

Page : 826-829

Keywords : Breast Cancer; Neural Networks; Mammographic Images; Wavelet process; GLCM Classification;

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Abstract

We present an application of artificial neural networks to mammographic images, aimed at improving early detection of sensitivity to breast cancer. The proposed application consists of two main steps: a pre-treatment step whose role is to extract the characteristics of the available mammographic images using the wavelet and co-occurrence (GLCM) matrices approach and a classification step based on an artificial neural network that uses these characteristics as input vectors for its training algorithm. The output of the training phase of this model is a categorization of the pre-treated images into three main groups: normal, benign and malignant. After the training phase, the network can be used in order to label new and unseen images as one of these three types.

Last modified: 2021-06-30 21:12:54