@inproceedings{chen2021semi,
  title={Semi-supervised semantic segmentation with cross pseudo supervision},
  author={Chen, Xiaokang and Yuan, Yuhui and Zeng, Gang and Wang, Jingdong},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={2613--2622},
  year={2021}
}

@article{luo2022semi-uncertainty,
  title={Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency},
  author={Luo, Xiangde and Wang, Guotai and Liao, Wenjun and Chen, Jieneng and Song, Tao and Chen, Yinan and Zhang, Shichuan and Metaxas, Dimitris N and Zhang, Shaoting},
  journal={Medical Image Analysis},
  volume={80},
  pages={102517},
  year={2022},
  publisher={Elsevier}
}

@inproceedings{luo2022semi-crossteaching,
  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},
  booktitle={International conference on medical imaging with deep learning},
  pages={820--833},
  year={2022},
  organization={PMLR}
}


@inproceedings{ronneberger2015u,
  title={U-net: Convolutional networks for biomedical image segmentation},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={Medical image computing and computer-assisted intervention--MICCAI 2015: 18th international conference, Munich, Germany, October 5-9, 2015, proceedings, part III 18},
  pages={234--241},
  year={2015},
  organization={Springer}
}

@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},
  publisher={Nature Publishing Group}
}

@article{ali2023multi,
  title={A multi-centre polyp detection and segmentation dataset for generalisability assessment},
  author={Ali, Sharib and Jha, Debesh and Ghatwary, Noha and Realdon, Stefano and Cannizzaro, Renato and Salem, Osama E and Lamarque, Dominique and Daul, Christian and Riegler, Michael A and Anonsen, Kim V and others},
  journal={Scientific Data},
  volume={10},
  number={1},
  pages={75},
  year={2023},
  publisher={Nature Publishing Group UK London}
}


@inproceedings{wang2024allspark,
  title={Allspark: Reborn labeled features from unlabeled in transformer for semi-supervised semantic segmentation},
  author={Wang, Haonan and Zhang, Qixiang and Li, Yi and Li, Xiaomeng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={3627--3636},
  year={2024}
}

@inproceedings{yang2023revisiting,
  title={Revisiting weak-to-strong consistency in semi-supervised semantic segmentation},
  author={Yang, Lihe and Qi, Lei and Feng, Litong and Zhang, Wayne and Shi, Yinghuan},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={7236--7246},
  year={2023}
}


@article{sohn2020fixmatch,
  title={Fixmatch: Simplifying semi-supervised learning with consistency and confidence},
  author={Sohn, Kihyuk and Berthelot, David and Carlini, Nicholas and Zhang, Zizhao and Zhang, Han and Raffel, Colin A and Cubuk, Ekin Dogus and Kurakin, Alexey and Li, Chun-Liang},
  journal={Advances in neural information processing systems},
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  pages={596--608},
  year={2020}
}
@inproceedings{wei2021shallow,
  title={Shallow attention network for polyp segmentation},
  author={Wei, Jun and Hu, Yiwen and Zhang, Ruimao and Li, Zhen and Zhou, S Kevin and Cui, Shuguang},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2021: 24th International Conference, Strasbourg, France, September 27--October 1, 2021, Proceedings, Part I 24},
  pages={699--708},
  year={2021},
  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}
}

@article{de2020complications,
  title={Complications of ureteroscopy: a complete overview},
  author={De Coninck, Vincent and Keller, Etienne Xavier and Somani, Bhaskar and Giusti, Guido and Proietti, Silvia and Rodriguez-Socarras, Moises and Rodr{\'\i}guez-Monsalve, Maria and Doizi, Steeve and Ventimiglia, Eugenio and Traxer, Olivier},
  journal={World journal of urology},
  volume={38},
  pages={2147--2166},
  year={2020},
  publisher={Springer}
}

@article{bretthauer2022effect,
  title={Effect of colonoscopy screening on risks of colorectal cancer and related death},
  author={Bretthauer, Michael and L{\o}berg, Magnus and Wieszczy, Paulina and Kalager, Mette and Emilsson, Louise and Garborg, Kjetil and Rupinski, Maciej and Dekker, Evelien and Spaander, Manon and Bugajski, Marek and others},
  journal={New England Journal of Medicine},
  volume={387},
  number={17},
  pages={1547--1556},
  year={2022},
  publisher={Mass Medical Soc}
}

@article{setia2023computer,
  title={Computer vision enabled segmentation of kidney stones during ureteroscopy and laser lithotripsy},
  author={Setia, Shaan A and Stoebner, Zachary A and Floyd, Chase and Lu, Daiwei and Oguz, Ipek and Kavoussi, Nicholas L},
  journal={Journal of Endourology},
  volume={37},
  number={4},
  pages={495--501},
  year={2023},
  publisher={Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New~…}
}

@inproceedings{arazo2020pseudo,
  title={Pseudo-labeling and confirmation bias in deep semi-supervised learning},
  author={Arazo, Eric and Ortego, Diego and Albert, Paul and O’Connor, Noel E and McGuinness, Kevin},
  booktitle={2020 International joint conference on neural networks (IJCNN)},
  pages={1--8},
  year={2020},
  organization={IEEE}
}

@article{luo2019real,
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  author={Luo, Huiyan and Xu, Guoliang and Li, Chaofeng and He, Longjun and Luo, Linna and Wang, Zixian and Jing, Bingzhong and Deng, Yishu and Jin, Ying and Li, Yin and others},
  journal={The Lancet Oncology},
  volume={20},
  number={12},
  pages={1645--1654},
  year={2019},
  publisher={Elsevier}
}



@inproceedings{yun2019cutmix,
  title={Cutmix: Regularization strategy to train strong classifiers with localizable features},
  author={Yun, Sangdoo and Han, Dongyoon and Oh, Seong Joon and Chun, Sanghyuk and Choe, Junsuk and Yoo, Youngjoon},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={6023--6032},
  year={2019}
}


@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={Medical image computing and computer assisted intervention--MICCAI 2019: 22nd international conference, Shenzhen, China, October 13--17, 2019, proceedings, part II 22},
  pages={605--613},
  year={2019},
  organization={Springer}
}
@inproceedings{liu2022moddrop++,
  title={Moddrop++: A dynamic filter network with intra-subject co-training for multiple sclerosis lesion segmentation with missing modalities},
  author={Liu, Han and Fan, Yubo and Li, Hao and Wang, Jiacheng and Hu, Dewei and Cui, Can and Lee, Ho Hin and Zhang, Huahong and Oguz, Ipek},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={444--453},
  year={2022},
  organization={Springer}
}
@article{kendall2017uncertainties,
  title={What uncertainties do we need in bayesian deep learning for computer vision?},
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  year={2017}
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@inproceedings{bellver2019budget,
  title={Budget-aware semi-supervised semantic and instance segmentation},
  author={Bellver Bueno, M{\'\i}riam and Salvador Aguilera, Amaia and Torres Vi{\~n}als, Jordi and Gir{\'o} Nieto, Xavier},
  booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019},
  pages={93--102},
  year={2019}
}

@inproceedings{zhang2018deep,
  title={Deep mutual learning},
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  pages={4320--4328},
  year={2018}
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@article{deol2024mp07,
  title={MP07-15 REAL-TIME KIDNEY STONE SEGMENTATION DURING DISTINCT URETEROSCOPIC TASKS USING A COMPUTER VISION MODEL},
  author={Deol, Ekamjit S and Lu, Daiwei and Oguz, Ipek and Kavoussi, Nicholas L},
  journal={Journal of Urology},
  volume={211},
  number={5S},
  pages={e110},
  year={2024},
  publisher={LWW}
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@article{chen2022debiased,
  title={Debiased self-training for semi-supervised learning},
  author={Chen, Baixu and Jiang, Junguang and Wang, Ximei and Wan, Pengfei and Wang, Jianmin and Long, Mingsheng},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={32424--32437},
  year={2022}
}

@inproceedings{wu2021semi,
  title={Semi-supervised left atrium segmentation with mutual consistency training},
  author={Wu, Yicheng and Xu, Minfeng and Ge, Zongyuan and Cai, Jianfei and Zhang, Lei},
  booktitle={Medical image computing and computer assisted intervention--MICCAI 2021: 24th international conference, Strasbourg, France, September 27--October 1, 2021, proceedings, part II 24},
  pages={297--306},
  year={2021},
  organization={Springer}
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@article{lei2022semi,
  title={Semi-supervised medical image segmentation using adversarial consistency learning and dynamic convolution network},
  author={Lei, Tao and Zhang, Dong and Du, Xiaogang and Wang, Xuan and Wan, Yong and Nandi, Asoke K},
  journal={IEEE transactions on medical imaging},
  volume={42},
  number={5},
  pages={1265--1277},
  year={2022},
  publisher={IEEE}
}

@inproceedings{wang2023ssl2,
  title={SSL2 Self-Supervised Learning meets semi-supervised learning: multiple clerosis segmentation in 7T-MRI from large-scale 3T-MRI},
  author={Wang, Jiacheng and Li, Hao and Liu, Han and Hu, Dewei and Lu, Daiwei and Yoon, Keejin and Barter, Kelsey and Bagnato, Francesca and Oguz, Ipek},
  booktitle={Medical Imaging 2023: Image Processing},
  volume={12464},
  pages={134--144},
  year={2023},
  organization={SPIE}
}

@inproceedings{li2025automated,
  title={Automated segmentation of central airway obstruction from endoscopic video stream with deep learning},
  author={Li, Hao and Wang, Jiacheng and Kumar, Nithin and d’Almeida, Jesse and Lu, Daiwei and Acar, Ayberk and Han, John and Yang, Qingyun and Ertop, Tayfun Efe and Wu, Jie Ying and others},
  booktitle={Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling},
  volume={13408},
  pages={113--119},
  year={2025},
  organization={SPIE}
}


@article{ji2022video,
  title={Video polyp segmentation: A deep learning perspective},
  author={Ji, Ge-Peng and Xiao, Guobao and Chou, Yu-Cheng and Fan, Deng-Ping and Zhao, Kai and Chen, Geng and Van Gool, Luc},
  journal={Machine Intelligence Research},
  volume={19},
  number={6},
  pages={531--549},
  year={2022},
  publisher={Springer}
}

@article{wang2025dynamic,
  title={Dynamic spectrum-driven hierarchical learning network for polyp segmentation},
  author={Wang, Haolin and Wang, Kai-Ni and Hua, Jie and Tang, Yi and Chen, Yang and Zhou, Guang-Quan and Li, Shuo},
  journal={Medical Image Analysis},
  volume={101},
  pages={103449},
  year={2025},
  publisher={Elsevier}
}


@inproceedings{tan2019efficientnet,
  title={Efficientnet: Rethinking model scaling for convolutional neural networks},
  author={Tan, Mingxing and Le, Quoc},
  booktitle={International conference on machine learning},
  pages={6105--6114},
  year={2019},
  organization={PMLR}
}