Automatic Brain MRI Classification Using Modified Ant Colony System and Neural Network Classifier

@article{Raghtate2015AutomaticBM,
  title={Automatic Brain MRI Classification Using Modified Ant Colony System and Neural Network Classifier},
  author={Ganesh S. Raghtate and Suresh S. Salankar},
  journal={2015 International Conference on Computational Intelligence and Communication Networks (CICN)},
  year={2015},
  pages={1241-1246}
}
In this paper, a hybrid intelligent machine learning technique for automatic classification of brain magnetic resonance images is presented. The proposed multistage technique involves the following computational methods, Otsu's method for skull removal, Fuzzy Inference System for image enhancement, Modified Fuzzy C Means with the Optimized Ant Colony System for image segmentation, Second Order Statistical Analysis and Wavelet Transform Method for feature extraction and the Feed Forward back… CONTINUE READING

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Key Quantitative Results

  • The accuracy rate of our proposed system is more than 99%.
  • Our proposal produced 99.50 % sensitivity, 99.17 % specificity and 99.33% classification accuracy for GLCM + FFNN classifier whereas 97.17 % sensitivity, 96.17 % specificity and 96.67% classification accuracy for the WT + FFNN classifier.

References

Publications referenced by this paper.
SHOWING 1-10 OF 19 REFERENCES

Content-based image classification using neural network

S. B. Park, J. W. Lee, S. K. Kim
  • Pattern Recognition 25
  • 2004
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Neural Networks for classification-A survey

G. P. Zhang
  • IEEE Transactions on Systems, Man & Cybernatics -Part C:Applications and Review 30
  • 2000
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Image classification of brain MRI using support vector machine

  • 2011 IEEE International Conference on Imaging Systems and Techniques
  • 2011
VIEW 2 EXCERPTS

Segmentation of brain MRI for tumor detection using ant colony optimization

A. Sheikh, R. K. Krishna
  • Proc. of Int. Colloquiums on Computer Electronics Electrical Mechanical and Civil
  • 2011
VIEW 3 EXCERPTS

Improved implementation of brain MRI image segmentation using Ant Colony System

  • 2010 IEEE International Conference on Computational Intelligence and Computing Research
  • 2010
VIEW 3 EXCERPTS