A Hybrid Approach for Automatic Classification of Brain MRI Using Genetic Algorithm and Support Vector Machine

@inproceedings{Kharrat2010AHA,
  title={A Hybrid Approach for Automatic Classification of Brain MRI Using Genetic Algorithm and Support Vector Machine},
  author={Ahmed Kharrat and Karim Gasmi and Mohamed Ben Messaoud and Nac{\'e}ra Benamrane and Mohamed Abid},
  year={2010}
}
We purpose a hybrid approach for classification of brain tissues in magnetic resonance images (MRI) based on genetic algorithm (GA) and support vector machine (SVM). A wavelet based texture feature set is derived. The optimal texture features are extracted from normal and tumor regions by using spatial gray level dependence method (SGLDM). These features are given as input to the SVM classifier. The choice of features, which constitute a big problem in classification techniques, is solved by… CONTINUE READING
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References

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Showing 1-10 of 23 references

Application of support vector machines on network abnormal intrusion detection

  • K. Zhang, H. X. CAO, H. Yan
  • Application Research of Computers,
  • 2006
1 Excerpt

Imaging techniques in neuro oncology

  • S. ArmstrongT., Z. CohenM., J. Weinbrg, R GilbertM.
  • Seminars in Oncology Nursing
  • 2004

, Support vector machines for diagnosis of breast tumors on US images

  • F. ChangR., J. WuW., K. MoonW., H. ChouY., R. ChenD.
  • Academic Radiology
  • 2003

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