Multi Intelligent Fuzzy Integration (Mifi) Support Vector Machines for the Mammogram Classification

  • Authors

    • G Jayandhi
    • Dr R.Dhaya
    • Dr R.Kanthavel
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18978
  • GLCM, Extreme Fuzzy Support Vector Machines, MIFI, Saliency Maps, Micro calcification, ROI Segmentation.

  • Breast cancer is the most important problem across the globe in which the 80% of the women are suffering without knowing the causes and effects of the cancer cells. Mammogram Image is the most powerful tool for the diagnosis of the Breast cancer. The analysis of this mammogram images proves to be more vital in terms of diagnosis but the accuracy level still needs improvisation. Several intelligent   techniques are suggested   for the detection of Micro calcification in mammogram images. The new technique MIFI-SVM has been proposed which integrates the GLCM features along with the Fuzzy Support Vector Machines. ROI Segmentation using Saliency maps has been used for the proposed algorithm and  feature is extracted using GLCM and fed to Fuzzy Support Vector Machines   The  MIAS datasets has been used for testing the proposed algorithm and accuracy, sensitivity has been measured which proves to be better when  compared to other  Multi-level SVM’s, C-SVM and Neural Networks.

     

     

  • References

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  • How to Cite

    Jayandhi, G., R.Dhaya, D., & R.Kanthavel, D. (2018). Multi Intelligent Fuzzy Integration (Mifi) Support Vector Machines for the Mammogram Classification. International Journal of Engineering & Technology, 7(3.34), 251-255. https://doi.org/10.14419/ijet.v7i3.34.18978