Modified Radial Basis Function Network for Brain Tumor Classification

  • S. N. Deepa
  • B. Aruna Devi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)


The study proposes a modified RBF with better network learning, convergence, error rates and classification results which involves spatial information data points using Gaussian Mixture Model (GMM) and Expectation Maximization (EM) algorithm for automatic biomedical brain tumour detection. The model was used to predict the brain tumour type (benign or malignant). The results showed outperformance of GMM-EM model with spatial points than the standard RBF model.A classification with a success of 85% and 90.3% has been obtained by the classifiers for RBF and RBF-GMM model.


Expectation Maximization Gaussian Mixture Model Radial Basis Function Network Expectation Maximization Algorithm Back Propagation Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • S. N. Deepa
    • 1
  • B. Aruna Devi
    • 1
  1. 1.Department of EEEAnna University of Technology, CoimbatoreCoimbatoreIndia

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