Brain Tumor Segmentation and Classification Using Deep Belief Network

@article{Jemimma2018BrainTS,
  title={Brain Tumor Segmentation and Classification Using Deep Belief Network},
  author={T. A. Jemimma and Y. Jacob Vetha Raj},
  journal={2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS)},
  year={2018},
  pages={1390-1394}
}
Brain image segmentation and classification is the significant area of research to differentiate the tumor region from the non-tumor region, for which the segmentation is an effective step that assures the effective classification. The ngeed for the accurate classification is initiated with the extract9ion of the relevant features, for which the segmentation p9lays a major role. In this paper, the segmentation is progressved using the Probabilistic Fuzzy C-means algorithm that distinguishes the… CONTINUE READING

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Key Quantitative Results

  • Experimentation is performed using the BRATS database and the proposed method is analyzed based on accuracy, sensitivity, and specificity that acquired the greater percentage of 95.78%, 96.8%, and 93.75%, respectively.

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