HOG Based Radial Basis Function Network for Brain MR Image Classification

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 31)

Abstract

Fully automated computer-aided diagnosis system is very much helpful for early detection and diagnosing of brain abnormalities like cancers and tumors. This paper presents two hybrid intelligent techniques such as HOG+PCA+RBFN and HOG+PCA+k-NN, which consists of four stages namely skull stripping, feature extraction, dimension reduction and classification. For efficient feature extraction Histograms of Oriented Gradients (HOG) method is used to extract the required feature vector and then the proposed techniques are used to classify images as normal or abnormal. The results show that the proposed technique gives an accuracy of 100 %, sensitivity of 99 % and specificity 100 %.

Keywords

Principal component analysis Histograms oriented gradients Magnetic resonance imaging Radial basis function network Skull stripping 

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Copyright information

© Springer India 2015

Authors and Affiliations

  • N. K. S. Behera
    • 1
  • M. K. Sahoo
    • 1
  • H. S. Behera
    • 1
  1. 1.Department of Computer Science Engineering and Information TechnologyVeer Surendra Sai University of TechnologyBurlaIndia

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