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A New Method Based-Gentle Adaboost and Wavelet Transform for Breast Cancer Classification

  • Nezha Hamdi
  • Khalid AuhmaniEmail author
  • Moha Mrabet Hassani
  • Omar Elkharki
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 914)

Abstract

In this paper we have realized a comparative study of mammograms classification accuracy based on a new Gentle Adaboost algorithm for different wavelet transforms and different features. Our proposition deals with the combination of a new Gentle Adaboost based algorithm with three wavelets transforms. In this new algorithm, the main classifier is realized by weighted weak classifiers. These weak classifiers are constructed from the sub-bands of discrete wavelet transform, stationary wavelet transform and double density wavelet transform. Used features are extracted from transformed mammograms. We have investigated the effect of these wavelet transforms combined with the extracted features on the classification accuracy. Receiver Operating Curves (ROC) tool is employed to evaluate the performance of the propositions. Mammograms of MIAS Database are used as samples to classify. True positive rate is plotted versus false positive rate for different types of features and for Gentle Adaboost iterations. Results showed that the best area under curve (AUC), is reached for Zernike moments combined with double density wavelet transform and it is equal to 1 for both t = 10 and t = 50.

Keywords

Artificial intelligence Image processing Machine learning Gentle Adaboost Wavelet transform ROC Feature extraction 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nezha Hamdi
    • 1
  • Khalid Auhmani
    • 2
    Email author
  • Moha Mrabet Hassani
    • 3
  • Omar Elkharki
    • 4
  1. 1.High Institute of Engineering and Business (ISGA)MarrakechMorocco
  2. 2.Department of Industrial Engineering, National School of Applied SciencesCadi Ayyad UniversitySafiMorocco
  3. 3.Department of Physics, Faculty of Sciences SemlaliaCadi Ayyad UniversityMarrakechMorocco
  4. 4.Faculty of Sciences and TechnologiesTangierMorocco

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