Lung nodule classification by the combination of fusion classifier and cascaded convolutional neural networks

@article{Sakamoto2018LungNC,
  title={Lung nodule classification by the combination of fusion classifier and cascaded convolutional neural networks},
  author={Masaharu Sakamoto and Hiroki Nakano and Kun Zhao and Taro Sekiyama},
  journal={2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)},
  year={2018},
  pages={822-825}
}
Lung nodule classification is a class imbalance problem, as nodules are found with much lower frequency than non-nodules. In the class imbalance problem, conventional classifiers tend to be overwhelmed by the majority class and ignore the minority class. We showed that cascaded convolutional neural networks can classify the nodule candidates precisely for a class imbalanced nodule candidate data set in our previous study. In this paper, we propose Fusion classifier in conjunction with the… Expand
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