@article{simpson2019MSD,
  title={A large annotated medical image dataset for the development and evaluation of segmentation algorithms},
  author={Simpson, Amber L and Antonelli, Michela and Bakas, Spyridon and Bilello, Michel and Farahani, Keyvan and Van Ginneken, Bram and Kopp-Schneider, Annette and Landman, Bennett A and Litjens, Geert and Menze, Bjoern and others},
  journal={arXiv preprint arXiv:1902.09063},
  year={2019}
}
@article{KiTSDataset,
  title={An international challenge to use artificial intelligence to define the state-of-the-art in kidney and kidney tumor segmentation in CT imaging.},
  author={Heller, Nicholas and McSweeney, Sean and Peterson, Matthew Thomas and Peterson, Sarah and Rickman, Jack and Stai, Bethany and Tejpaul, Resha and Oestreich, Makinna and Blake, Paul and Rosenberg, Joel and others},
  volume = {38},
    number = {6},
    pages = {626-626},
    year = {2020},
  journal={American Society of Clinical Oncology}
}
@misc{NIHPancreas,
  title = {{NIH Pancreas}},
  howpublished = "\url{https://wiki.cancerimagingarchive.net/display/Public/Pancreas-CT}",
  year = {2020},
  note = "[Online; Accessed: Aug. 2020]"
}
@inproceedings{ronneberger2015u,
  title={U-net: Convolutional networks for biomedical image segmentation},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={234--241},
  year={2015}
}

@article{AbdomenCT-1K,
  title={AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?},
  author={Ma, Jun and Zhang, Yao and Gu, Song and Zhu, Cheng and Ge, Cheng and Zhang, Yichi and An, Xingle and Wang, Congcong and Wang, Qiyuan and Liu, Xin and Cao, Shucheng and Zhang, Qi and Liu, Shangqing and Wang, Yunpeng and Li, Yuhui and He, Jian and Yang, Xiaoping},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2021},
  doi={10.1109/TPAMI.2021.3100536}
}


@article{isensee2021nnu,
  title={nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation},
  author={Isensee, Fabian and Jaeger, Paul F and Kohl, Simon AA and Petersen, Jens and Maier-Hein, Klaus H},
  journal={Nature Methods},
  volume={18},
  number={2},
  pages={203--211},
  year={2021}
}

@article{LossOdyssey,
title = {Loss Odyssey in Medical Image Segmentation},
journal = {Medical Image Analysis},
volume = {71},
pages = {102035},
year = {2021},
author = {Jun Ma and Jianan Chen and Matthew Ng and Rui Huang and Yu Li and Chen Li and Xiaoping Yang and Anne L. Martel}
}

@article{bilic2019lits,
  title={The liver tumor segmentation benchmark (lits)},
  author={Bilic, Patrick and Christ, Patrick Ferdinand and Vorontsov, Eugene and Chlebus, Grzegorz and Chen, Hao and Dou, Qi and Fu, Chi-Wing and Han, Xiao and Heng, Pheng-Ann and Hesser, J{\"u}rgen and others},
  journal={arXiv preprint arXiv:1901.04056},
  year={2019}
}


@article{KiTS,
  title={The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge},
  author={Heller, Nicholas and Isensee, Fabian and Maier-Hein, Klaus H and Hou, Xiaoshuai and Xie, Chunmei and Li, Fengyi and Nan, Yang and Mu, Guangrui and Lin, Zhiyong and Han, Miofei and others},
  journal={Medical Image Analysis},
  volume={67},
  pages={101821},
  year={2021},
}
@misc{roth9data,
  title={Data from Pancreas-CT. The Cancer Imaging Archive (2016)},
  author={Roth, H and Farag, A and Turkbey, EB and Lu, L and Liu, J and Summers, RM}
}
@inproceedings{roth2015deeporgan,
  title={Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation},
  author={Roth, Holger R and Lu, Le and Farag, Amal and Shin, Hoo-Chang and Liu, Jiamin and Turkbey, Evrim B and Summers, Ronald M},
  booktitle={International conference on medical image computing and computer-assisted intervention},
  pages={556--564},
  year={2015},
  organization={Springer}
}
@article{clark2013TCIA,
  title={The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository},
  author={Clark, Kenneth and Vendt, Bruce and Smith, Kirk and Freymann, John and Kirby, Justin and Koppel, Paul and Moore, Stephen and Phillips, Stanley and Maffitt, David and Pringle, Michael and others},
  journal={Journal of Digital Imaging},
  volume={26},
  number={6},
  pages={1045--1057},
  year={2013}
}

@incollection{zhou2018unet++,
  title={Unet++: A nested u-net architecture for medical image segmentation},
  author={Zhou, Zongwei and Siddiquee, Md Mahfuzur Rahman and Tajbakhsh, Nima and Liang, Jianming},
  booktitle={Deep learning in medical image analysis and multimodal learning for clinical decision support},
  pages={3--11},
  year={2018},
  publisher={Springer}
}

@misc{ssl4mis2020,
  title={{SSL4MIS}},
  author={Luo, Xiangde},
  howpublished={\url{https://github.com/HiLab-git/SSL4MIS}},
  year={2020}}
  
@article{chen2021transunet,
  title={Transunet: Transformers make strong encoders for medical image segmentation},
  author={Chen, Jieneng and Lu, Yongyi and Yu, Qihang and Luo, Xiangde and Adeli, Ehsan and Wang, Yan and Lu, Le and Yuille, Alan L and Zhou, Yuyin},
  journal={arXiv preprint arXiv:2102.04306},
  year={2021}
}

@inproceedings{yu2019uncertainty,
  title={Uncertainty-aware self-ensembling model for semi-supervised 3D left atrium segmentation},
  author={Yu, Lequan and Wang, Shujun and Li, Xiaomeng and Fu, Chi-Wing and Heng, Pheng-Ann},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={605--613},
  year={2019},
  organization={Springer}
}

@article{tarvainen2017mean,
  title={Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results},
  author={Tarvainen, Antti and Valpola, Harri},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{reiss2021every,
  title={Every annotation counts: Multi-label deep supervision for medical image segmentation},
  author={Rei{\ss}, Simon and Seibold, Constantin and Freytag, Alexander and Rodner, Erik and Stiefelhagen, Rainer},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={9532--9542},
  year={2021}
}

@article{you2022simcvd,
  title={Simcvd: Simple contrastive voxel-wise representation distillation for semi-supervised medical image segmentation},
  author={You, Chenyu and Zhou, Yuan and Zhao, Ruihan and Staib, Lawrence and Duncan, James S},
  journal={IEEE Transactions on Medical Imaging},
  year={2022},
  publisher={IEEE}
}

@article{wang2021semi,
  title={Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention},
  author={Wang, Guotai and Zhai, Shuwei and Lasio, Giovanni and Zhang, Baoshe and Yi, Byong and Chen, Shifeng and Macvittie, Thomas J and Metaxas, Dimitris and Zhou, Jinghao and Zhang, Shaoting},
  journal={IEEE transactions on medical imaging},
  year={2021},
  publisher={IEEE}
}

@article{hu2020coarse,
  title={Coarse-to-fine adversarial networks and zone-based uncertainty analysis for NK/T-cell lymphoma segmentation in CT/PET images},
  author={Hu, Xiaobin and Guo, Rui and Chen, Jieneng and Li, Hongwei and Waldmannstetter, Diana and Zhao, Yu and Li, Biao and Shi, Kuangyu and Menze, Bjoern},
  journal={IEEE journal of biomedical and health informatics},
  volume={24},
  number={9},
  pages={2599--2608},
  year={2020},
  publisher={IEEE}
}

@article{peng2021self,
  title={Self-paced contrastive learning for semi-supervised medical image segmentation with meta-labels},
  author={Peng, Jizong and Wang, Ping and Desrosiers, Christian and Pedersoli, Marco},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  year={2021}
}

@misc{MONAI_Consortium_MONAI_Medical_Open_2020,
author = {MONAI Consortium},
doi = {10.5281/zenodo.4323058},
month = {3},
title = {MONAI: Medical Open Network for AI},
url = {https://github.com/Project-MONAI/MONAI},
year = {2020}
}

@article{luo2021semi,
  title={Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer},
  author={Luo, Xiangde and Hu, Minhao and Song, Tao and Wang, Guotai and Zhang, Shaoting},
  journal={arXiv preprint arXiv:2112.04894},
  year={2021}
}
