Towards Automatic 3D Shape Instantiation for Deployed Stent Grafts: 2D Multiple-class and Class-imbalance Marker Segmentation with Equally-weighted Focal U-Net

Xiao-Yun Zhou, Celia V. Riga, Su-Lin Lee, Guang-Zhong Yang. Towards Automatic 3D Shape Instantiation for Deployed Stent Grafts: 2D Multiple-class and Class-imbalance Marker Segmentation with Equally-weighted Focal U-Net. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018, Madrid, Spain, October 1-5, 2018. pages 1261-1267, IEEE, 2018. [doi]

@inproceedings{ZhouRLY18,
  title = {Towards Automatic 3D Shape Instantiation for Deployed Stent Grafts: 2D Multiple-class and Class-imbalance Marker Segmentation with Equally-weighted Focal U-Net},
  author = {Xiao-Yun Zhou and Celia V. Riga and Su-Lin Lee and Guang-Zhong Yang},
  year = {2018},
  doi = {10.1109/IROS.2018.8594178},
  url = {https://doi.org/10.1109/IROS.2018.8594178},
  researchr = {https://researchr.org/publication/ZhouRLY18},
  cites = {0},
  citedby = {0},
  pages = {1261-1267},
  booktitle = {2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018, Madrid, Spain, October 1-5, 2018},
  publisher = {IEEE},
  isbn = {978-1-5386-8094-0},
}