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Detection and Classification of Breast Cancer using Support Vector Machine and Artificial Neural Network using Contourlet Transform


Affiliations
1 Department of Information Science and Engineering, BNM Institute of Technology, India
     

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The technique of image processing is applied to diagnose breast cancer from digital mammogram image. The proposed work uses Contourlet transform to decompose the given gray-scale image. The spatial (textual and statistical) features are been extracted along with frequency domain coefficients. GLCM is the method used for extracting the feature values. Classification of image using support vector machine or artificial neural network classifiers is performed.

Keywords

Mammographic Images, Support Vector Machine (SVM), Feature Extraction, Contourlet Transform (CT), Gray Level Co-Occurrence Matrix (GLCM), Artificial Neural Network (ANN).
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  • Detection and Classification of Breast Cancer using Support Vector Machine and Artificial Neural Network using Contourlet Transform

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Authors

Soumya Hundekar
Department of Information Science and Engineering, BNM Institute of Technology, India
Saritha Chakrasali
Department of Information Science and Engineering, BNM Institute of Technology, India

Abstract


The technique of image processing is applied to diagnose breast cancer from digital mammogram image. The proposed work uses Contourlet transform to decompose the given gray-scale image. The spatial (textual and statistical) features are been extracted along with frequency domain coefficients. GLCM is the method used for extracting the feature values. Classification of image using support vector machine or artificial neural network classifiers is performed.

Keywords


Mammographic Images, Support Vector Machine (SVM), Feature Extraction, Contourlet Transform (CT), Gray Level Co-Occurrence Matrix (GLCM), Artificial Neural Network (ANN).

References