Abstract: Neural Systems Approach for Ammography Finding by Utilizing Wavelet Features
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064

Downloads: 102

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014

Neural Systems Approach for Ammography Finding by Utilizing Wavelet Features

A. Mallareddy, A. Priyanka

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.

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

Edition: Volume 3 Issue 11, November 2014

Pages: 826 - 829

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How to Cite this Article?

A. Mallareddy, A. Priyanka, "Neural Systems Approach for Ammography Finding by Utilizing Wavelet Features", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=OCT14879, Volume 3 Issue 11, November 2014, 826 - 829

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