Classification of the thyroid nodules using support vector machines

@article{Chang2008ClassificationOT,
  title={Classification of the thyroid nodules using support vector machines},
  author={Chuan-Yu Chang and Ming-Feng Tsai and Shao-Jer Chen},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={3093-3098}
}
Most of the thyroid nodules are heterogeneous with various internal components, which confuse many radiologists and physicians with their various echo patterns in thyroid nodules. A lot of texture extraction methods were used to characterize the thyroid nodules. Accordingly, the thyroid nodules could be classified by the corresponding textural features. In this paper, five support vector machines (SVM) were adopted to select the significant textural features and to classify the nodular lesions… CONTINUE READING
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