H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes

@article{Li2018HDenseUNetHD,
  title={H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes},
  author={X. Li and H. Chen and Xiaojuan Qi and Q. Dou and Chi-Wing Fu and P. Heng},
  journal={IEEE Transactions on Medical Imaging},
  year={2018},
  volume={37},
  pages={2663-2674}
}
  • X. Li, H. Chen, +3 authors P. Heng
  • Published 2018
  • Computer Science, Medicine
  • IEEE Transactions on Medical Imaging
Liver cancer is one of the leading causes of cancer death. [...] Key Method We formulate the learning process of the H-DenseUNet in an end-to-end manner, where the intra-slice representations and inter-slice features can be jointly optimized through a hybrid feature fusion layer. We extensively evaluated our method on the data set of the MICCAI 2017 Liver Tumor Segmentation Challenge and 3DIRCADb data set. Our method outperformed other state-of-the-arts on the segmentation results of tumors and achieved very…Expand
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