@article{simpson2019MSD,
author = {Amber L. Simpson and Michela Antonelli and Spyridon Bakas and Michel Bilello and Keyvan Farahani and Bram van Ginneken and Annette Kopp-Schneider and Bennett A. Landman and Geert Litjens and Bjoern Menze and Olaf Ronneberger and Ronald M. Summers and Patrick Bilic and Patrick F. Christ and Richard K. G. Do and Marc Gollub and Jennifer Golia-Pernicka and Stephan H. Heckers and William R. Jarnagin and Maureen K. McHugo and Sandy Napel and Eugene Vorontsov and Lena Maier-Hein and M. Jorge Cardoso},
title = {A large annotated medical image dataset for the development and evaluation of segmentation algorithms},
year = {2019},
journal = {arXiv preprint arXiv:1902.09063},
}

@article{KiTS,
title = {The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge},
journal = {Medical Image Analysis},
volume = {67},
pages = {101821},
year = {2021},
author = {Nicholas Heller and Fabian Isensee and Klaus H. Maier-Hein and Xiaoshuai Hou and Chunmei Xie and Fengyi Li and Yang Nan and Guangrui Mu and Zhiyong Lin and Miofei Han and Guang Yao and Yaozong Gao and Yao Zhang and Yixin Wang and Feng Hou and Jiawei Yang and Guangwei Xiong and Jiang Tian and Cheng Zhong and Jun Ma and Jack Rickman and Joshua Dean and Bethany Stai and Resha Tejpaul and Makinna Oestreich and Paul Blake and Heather Kaluzniak and Shaneabbas Raza and Joel Rosenberg and Keenan Moore and Edward Walczak and Zachary Rengel and Zach Edgerton and Ranveer Vasdev and Matthew Peterson and Sean McSweeney and Sarah Peterson and Arveen Kalapara and Niranjan Sathianathen and Nikolaos Papanikolopoulos and Christopher Weight}
}


@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}
}



@inproceedings{U-Net,
  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},
  volume={44},
  number={10},
  pages={6695-6714},
  year={2022}
}


@article{MedIA-FLARE21,
title = {Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge},
author = {Jun Ma and Yao Zhang and Song Gu and Xingle An and Zhihe Wang and Cheng Ge and Congcong Wang and Fan Zhang and Yu Wang and Yinan Xu and Shuiping Gou and Franz Thaler and Christian Payer and Darko Štern and Edward G.A. Henderson and Dónal M. McSweeney and Andrew Green and Price Jackson and Lachlan McIntosh and Quoc-Cuong Nguyen and Abdul Qayyum and Pierre-Henri Conze and Ziyan Huang and Ziqi Zhou and Deng-Ping Fan and Huan Xiong and Guoqiang Dong and Qiongjie Zhu and Jian He and Xiaoping Yang},
journal = {Medical Image Analysis},
volume = {82},
pages = {102616},
year = {2022}
}

@inproceedings{FLARE22-1st-Huang,
  title={Revisiting nnU-net for iterative pseudo labeling and efficient sliding window inference},
  author={Huang, Ziyan and Wang, Haoyu and Ye, Jin and Niu, Jingqi and Tu, Can and Yang, Yuncheng and Du, Shiyi and Deng, Zhongying and Gu, Lixu and He, Junjun},
  booktitle={MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation},
  pages={178--189},
  year={2022},
  publisher={Springer}
}

@inproceedings{FLARE22-bestDSC-Wang,
  title={Cascade dual-decoders network for abdominal organs segmentation},
  author={Wang, Ershuai and Zhao, Yaliang and Wu, Yajun},
  booktitle={MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation},
  pages={202--213},
  year={2022},
  publisher={Springer},
}

@article{FLARE22,
    author = {Jun Ma and Yao Zhang and Song Gu and Cheng Ge and Shihao Ma and Adamo Young and Cheng Zhu and Kangkang Meng and Xin Yang and Ziyan Huang and Fan Zhang and Wentao Liu and YuanKe Pan and Shoujin Huang and Jiacheng Wang and Mingze Sun and Weixin Xu and Dengqiang Jia and Jae Won Choi and Natália Alves and Bram de Wilde and Gregor Koehler and Yajun Wu and Manuel Wiesenfarth and Qiongjie Zhu and Guoqiang Dong and Jian He and the FLARE Challenge Consortium and Bo Wang},
    title = {Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge},
    year = {2023},
    journal = {arXiv preprint arXiv:2308.05862},
}

@article{MedSAM,
  title={Segment Anything in Medical Images},
  author={Ma, Jun and Wang, Bo},
  journal={arXiv preprint arXiv:2304.12306},
  year={2023}
}

@article{nnUNet,
  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{LiTS,
    title = {The Liver Tumor Segmentation Benchmark (LiTS)},
    journal = {Medical Image Analysis},
    volume = {84},
    pages = {102680},
    year = {2023},
    author = {Patrick Bilic and Patrick Christ and Hongwei Bran Li and Eugene Vorontsov and Avi Ben-Cohen and Georgios Kaissis and Adi Szeskin and Colin Jacobs and Gabriel Efrain Humpire Mamani and Gabriel Chartrand and Fabian Lohöfer and Julian Walter Holch and Wieland Sommer and Felix Hofmann and Alexandre Hostettler and Naama Lev-Cohain and Michal Drozdzal and Michal Marianne Amitai and Refael Vivanti and Jacob Sosna and Ivan Ezhov and Anjany Sekuboyina and Fernando Navarro and Florian Kofler and Johannes C. Paetzold and Suprosanna Shit and Xiaobin Hu and Jana Lipková and Markus Rempfler and Marie Piraud and Jan Kirschke and Benedikt Wiestler and Zhiheng Zhang and Christian Hülsemeyer and Marcel Beetz and Florian Ettlinger and Michela Antonelli and Woong Bae and Míriam Bellver and Lei Bi and Hao Chen and Grzegorz Chlebus and Erik B. Dam and Qi Dou and Chi-Wing Fu and Bogdan Georgescu and Xavier Giró-i-Nieto and Felix Gruen and Xu Han and Pheng-Ann Heng and Jürgen Hesser and Jan Hendrik Moltz and Christian Igel and Fabian Isensee and Paul Jäger and Fucang Jia and Krishna Chaitanya Kaluva and Mahendra Khened and Ildoo Kim and Jae-Hun Kim and Sungwoong Kim and Simon Kohl and Tomasz Konopczynski and Avinash Kori and Ganapathy Krishnamurthi and Fan Li and Hongchao Li and Junbo Li and Xiaomeng Li and John Lowengrub and Jun Ma and Klaus Maier-Hein and Kevis-Kokitsi Maninis and Hans Meine and Dorit Merhof and Akshay Pai and Mathias Perslev and Jens Petersen and Jordi Pont-Tuset and Jin Qi and Xiaojuan Qi and Oliver Rippel and Karsten Roth and Ignacio Sarasua and Andrea Schenk and Zengming Shen and Jordi Torres and Christian Wachinger and Chunliang Wang and Leon Weninger and Jianrong Wu and Daguang Xu and Xiaoping Yang and Simon Chun-Ho Yu and Yading Yuan and Miao Yue and Liping Zhang and Jorge Cardoso and Spyridon Bakas and Rickmer Braren and Volker Heinemann and Christopher Pal and An Tang and Samuel Kadoury and Luc Soler and Bram {van Ginneken} and Hayit Greenspan and Leo Joskowicz and Bjoern Menze},
}


@article{TotalSegmentator,
author = {Wasserthal, Jakob and Breit, Hanns-Christian and Meyer, Manfred T. and Pradella, Maurice and Hinck, Daniel and Sauter, Alexander W. and Heye, Tobias and Boll, Daniel T. and Cyriac, Joshy and Yang, Shan and Bach, Michael and Segeroth, Martin},
title = {TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images},
journal = {Radiology: Artificial Intelligence},
volume = {5},
number = {5},
pages = {e230024},
year = {2023}
}

@article{autoPET-Data,
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  journal={Scientific Data},
  volume={9},
  number={1},
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  year={2022}
}

@article{autoPET-MICCAI22,
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  journal={preprint at Research Square (Nature Portfolio )},
  doi={https://doi.org/10.21203/rs.3.rs-2572595/v1},
  year={2023}
}


@article{TCIA,
  title={The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository},
  author={Clark, Ken and Vendt, Bruce and Smith, Kirk and Freymann, John and Kirby, Justin and Koppel, Paul and Moore, Stephen and Phillips, Stephen and Maffitt, Derek and Pringle, Michael and Tarbox, Lawrence and Prior, Fred},
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@inproceedings{ITKSNAP,
  title={ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images},
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  booktitle={Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  pages={3342--3345},
  year={2016}
}


@article{codalab,
  author  = {Adrien Pavao and Isabelle Guyon and Anne-Catherine Letournel and Dinh-Tuan Tran and Xavier Baro and Hugo Jair Escalante and Sergio Escalera and Tyler Thomas and Zhen Xu},
  title   = {CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges},
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@inproceedings{BTCV,
  title={Miccai multi-atlas labeling beyond the cranial vault--workshop and challenge},
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@inproceedings{UNETR,
  title={Unetr: Transformers for 3d medical image segmentation},
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  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
  pages={574--584},
  year={2022}
}

@inproceedings{SwinUNETR,
  title={Self-supervised pre-training of swin transformers for 3d medical image analysis},
  author={Tang, Yucheng and Yang, Dong and Li, Wenqi and Roth, Holger R and Landman, Bennett and Xu, Daguang and Nath, Vishwesh and Hatamizadeh, Ali},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={20730--20740},
  year={2022}
}

@inproceedings{3dU-Net,
  title={3D U-Net: learning dense volumetric segmentation from sparse annotation},
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  year={2016},
  organization={Springer}
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@inproceedings{VNet,
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@inproceedings{MAE,
  title={Masked autoencoders are scalable vision learners},
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  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
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  year={2022}
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@inproceedings{med3dmae,
  title={Masked image modeling advances 3d medical image analysis},
  author={Chen, Zekai and Agarwal, Devansh and Aggarwal, Kshitij and Safta, Wiem and Balan, Mariann Micsinai and Brown, Kevin},
  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
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@incollection{CascadeDual-decoders,
  title={Cascade dual-decoders network for abdominal organs segmentation},
  author={Wang, Ershuai and Zhao, Yaliang and Wu, Yajun},
  booktitle={MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation},
  pages={202--213},
  year={2022},
  publisher={Springer}
}

@incollection{self-training,
  title={Self-training with Selective Re-training Improves Abdominal Organ Segmentation in CT Image},
  author={Zhang, Fan and Wang, Meihuan and Yang, Hua},
  booktitle={MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation},
  pages={1--10},
  year={2022},
  publisher={Springer}
}

@incollection{HybridArchitecture,
  title={Combining Self-training and Hybrid Architecture for Semi-supervised Abdominal Organ Segmentation},
  author={Liu, Wentao and Xu, Weijin and Yan, Songlin and Wang, Lemeng and Li, Haoyuan and Yang, Huihua},
  booktitle={MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation},
  pages={281--292},
  year={2022},
  publisher={Springer}
}

@article{MSD,
  title={The medical segmentation decathlon},
  author={Antonelli, Michela and Reinke, Annika and Bakas, Spyridon and Farahani, Keyvan and Kopp-Schneider, Annette and Landman, Bennett A and Litjens, Geert and Menze, Bjoern and Ronneberger, Olaf and Summers, Ronald M and others},
  journal={Nature Communications},
  volume={13},
  number={1},
  pages={4128},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@inproceedings{DoDNet,
  title={DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets},
  author={Zhang, Jianpeng and Xie, Yutong and Xia, Yong and Shen, Chunhua},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={1195--1204},
  year={2021}
}

@article{conditional_nnU-Net,
  title={Multiorgan segmentation from partially labeled datasets with conditional nnU-Net},
  author={Zhang, Guobin and Yang, Zhiyong and Huo, Bin and Chai, Shude and Jiang, Shan},
  journal={Computers in Biology and Medicine},
  volume={136},
  pages={104658},
  year={2021},
  publisher={Elsevier}
}

@article{MFUnetr,
  title={MFUnetr: A transformer-based multi-task learning network for multi-organ segmentation from partially labeled datasets},
  author={Hao, Qin and Tian, Shengwei and Yu, Long and Wang, Junwen},
  journal={Biomedical Signal Processing and Control},
  volume={85},
  pages={105081},
  year={2023},
  publisher={Elsevier}
}

@proceedings{FLARE22book,
  editor       = {Jun Ma and
                  Bo Wang},
  title        = {Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation
                  - {MICCAI} 2022 Challenge, {FLARE} 2022, Held in Conjunction with
                  {MICCAI} 2022, Singapore, September 22, 2022, Proceedings},
  series       = {Lecture Notes in Computer Science},
  volume       = {13816},
  publisher    = {Springer},
  year         = {2022},
  url          = {https://doi.org/10.1007/978-3-031-23911-3},
  doi          = {10.1007/978-3-031-23911-3},
  isbn         = {978-3-031-23910-6},
  timestamp    = {Thu, 02 Feb 2023 00:00:00 +0100},
  biburl       = {https://dblp.org/rec/conf/miccai/2022flare.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}