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	title = {Cross-{Mix} {Monitoring} for {Medical} {Image} {Segmentation} {With} {Limited} {Supervision}},
	volume = {25},
	issn = {1520-9210},
	url = {https://doi.org/10.1109/TMM.2022.3154159},
	doi = {10.1109/TMM.2022.3154159},
	journal = {Trans. Multi.},
	author = {Shu, Yucheng and Li, Hengbo and Xiao, Bin and Bi, Xiuli and Li, Weisheng},
	month = jan,
	year = {2023},
	pages = {1700--1712}
}

@inproceedings{yang_st_2022,
	address = {New Orleans, LA, USA},
	title = {{ST}++: {Make} {Self}-{trainingWork} {Better} for {Semi}-supervised {Semantic} {Segmentation}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {978-1-6654-6946-3},
	shorttitle = {{ST}++},
	url = {https://ieeexplore.ieee.org/document/9880151/},
	doi = {10.1109/CVPR52688.2022.00423},
	booktitle = {2022 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Yang, Lihe and Zhuo, Wei and Qi, Lei and Shi, Yinghuan and Gao, Yang},
	month = jun,
	year = {2022},
	pages = {4258--4267}
}

@inproceedings{zou_pseudoseg_2021,
  title={PseudoSeg: {Designing} {Pseudo} {Labels} for {Semantic Segmentation}},
  author={Zou, Yuliang and others},
  booktitle={International Conference on Learning Representations},
  year={2021}
}

@inproceedings{liu_perturbed_2022,
	address = {New Orleans, LA, USA},
	title = {Perturbed and {Strict} {Mean} {Teachers} for {Semi}-supervised {Semantic} {Segmentation}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {978-1-6654-6946-3},
	url = {https://ieeexplore.ieee.org/document/9879201/},
	doi = {10.1109/CVPR52688.2022.00422},
	booktitle = {2022 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Liu, Yuyuan and others},
	month = jun,
	year = {2022},
	pages = {4248--4257}
}

@inproceedings{chen_semi-supervised_2021,
	address = {Nashville, TN, USA},
	title = {Semi-{Supervised} {Semantic} {Segmentation} with {Cross} {Pseudo} {Supervision}},
	copyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},
	isbn = {978-1-6654-4509-2},
	url = {https://ieeexplore.ieee.org/document/9577639/},
	doi = {10.1109/CVPR46437.2021.00264},
	booktitle = {2021 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Chen, Xiaokang and Yuan, Yuhui and Zeng, Gang and Wang, Jingdong},
	month = jun,
	year = {2021},
	pages = {2613--2622}
}

@inproceedings{luo_semi-supervised_2022,
	title = {Semi-{Supervised} {Medical} {Image} {Segmentation} via {Cross} {Teaching} between {CNN} and {Transformer}},
	url = {https://proceedings.mlr.press/v172/luo22b.html},
	booktitle = {Proceedings of {The} 5th {International} {Conference} on {Medical} {Imaging} with {Deep} {Learning}},
	publisher = {PMLR},
	author = {Luo, Xiangde and Hu, Minhao and Song, Tao and Wang, Guotai and Zhang, Shaoting},
	month = dec,
	year = {2022},
	note = {ISSN: 2640-3498},
	pages = {820--833},
}

@article{yang_semi-supervised_2024,
	title = {Semi-supervised medical image segmentation via cross teaching between {MobileNet} and {MobileViT}},
	volume = {150},
	issn = {0262-8856},
	url = {https://doi.org/10.1016/j.imavis.2024.105196},
	doi = {10.1016/j.imavis.2024.105196},
	number = {C},
	journal = {Image Vision Comput.},
	author = {Yang, Yuan and Zhang, Lin and Ren, Lei},
	month = oct,
	year = {2024},
}

@inproceedings{chi_adaptive_2024,
	address = {Seattle, WA, USA},
	title = {Adaptive {Bidirectional} {Displacement} for {Semi}-{Supervised} {Medical} {Image} {Segmentation}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {979-8-3503-5300-6},
	url = {https://ieeexplore.ieee.org/document/10658193/},
	doi = {10.1109/CVPR52733.2024.00390},
	booktitle = {2024 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Chi, Hanyang and Pang, Jian and Zhang, Bingfeng and Liu, Weifeng},
	month = jun,
	year = {2024},
	pages = {4070--4080},
}

@inproceedings{kirillov_segment_2023,
	address = {Paris, France},
	title = {Segment {Anything}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {979-8-3503-0718-4},
	url = {https://ieeexplore.ieee.org/document/10378323/},
	doi = {10.1109/ICCV51070.2023.00371},
	booktitle = {2023 {IEEE}/{CVF} {International} {Conference} on {Computer} {Vision} ({ICCV})},
	publisher = {IEEE},
	author = {Kirillov, Alexander and others},
	month = oct,
	year = {2023},
	pages = {3992--4003},
}

@article{wang_sam-med3d_2025,
	title = {{SAM}-{Med3D}: {A} {Vision} {Foundation} {Model} for {General}-{Purpose} {Segmentation} on {Volumetric} {Medical} {Images}},
	volume = {36},
	issn = {2162-2388},
	shorttitle = {{SAM}-{Med3D}},
	url = {https://ieeexplore.ieee.org/document/11105528},
	doi = {10.1109/TNNLS.2025.3586694},
	number = {10},
	journal = {IEEE Transactions on Neural Networks and Learning Systems},
	author = {Wang, Haoyu and others},
	month = oct,
	year = {2025},
	pages = {17599--17612},
}

@misc{ma_medsam2_2025,
	title = {{MedSAM2}: {Segment} {Anything} in {3D} {Medical} {Images} and {Videos}},
	shorttitle = {{MedSAM2}},
	url = {http://arxiv.org/abs/2504.03600},
	doi = {10.48550/arXiv.2504.03600},
	publisher = {arXiv},
	author = {Ma, Jun and others},
	month = apr,
	year = {2025},
	note = {arXiv:2504.03600 [eess]},
}

@inproceedings{ma_steady_2025,
	title = {Steady {Progress} {Beats} {Stagnation}: {Mutual} {Aid} of {Foundation} and {Conventional} {Models} in {Mixed} {Domain} {Semi}-{Supervised} {Medical} {Image} {Segmentation}},
	shorttitle = {Steady {Progress} {Beats} {Stagnation}},
	url = {https://ieeexplore.ieee.org/document/11094453},
	doi = {10.1109/CVPR52734.2025.00488},
	booktitle = {2025 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	author = {Ma, Qinghe and others},
	month = jun,
	year = {2025},
	note = {ISSN: 2575-7075},
	keywords = {Biomedical imaging, Computer vision, Convergence, domain shift, Foundation models, Image segmentation, medical image segmentation, Optimization, Pattern recognition, Reliability, semi-supervised learning, Training, Visualization},
	pages = {5175--5185},
}

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	copyright = {2014 The Author(s)},
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	url = {https://www.nature.com/articles/ncomms5006},
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	urldate = {2025-12-05},
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	author = {Aerts, Hugo J. W. L. and others},
	month = jun,
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	note = {Publisher: Nature Publishing Group},
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	pages = {4006},
}

@article{campello_multi-centre_2021,
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	issn = {1558-254X},
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	url = {https://ieeexplore.ieee.org/document/9458279},
	doi = {10.1109/TMI.2021.3090082},
	number = {12},
	journal = {IEEE Transactions on Medical Imaging},
	author = {Campello, Víctor M. and others},
	month = dec,
	year = {2021},
	keywords = {Biomedical engineering, Cardiovascular magnetic resonance, data augmentation, deep learning, Deep learning, domain adaption, generalizability, Heart, Hospitals, image segmentation, Image segmentation, Protocols, public dataset, Training},
	pages = {3543--3554},
}

@article{litjens_evaluation_2014,
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	volume = {18},
	issn = {1361-8415},
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	url = {https://www.sciencedirect.com/science/article/pii/S1361841513001734},
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	month = feb,
	year = {2014},
	keywords = {Challenge, MRI, Prostate, Segmentation},
	pages = {359--373},
}

@inproceedings{ronneberger_u-net_2015,
	address = {Cham},
	title = {U-{Net}: {Convolutional} {Networks} for {Biomedical} {Image} {Segmentation}},
	isbn = {978-3-319-24574-4},
	shorttitle = {U-{Net}},
	doi = {10.1007/978-3-319-24574-4_28},
	booktitle = {Medical {Image} {Computing} and {Computer}-{Assisted} {Intervention} – {MICCAI} 2015},
	publisher = {Springer International Publishing},
	author = {Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
	year = {2015},
	keywords = {Convolutional Layer, Data Augmentation, Deep Network, Ground Truth Segmentation, Training Image},
	pages = {234--241},
}

@misc{hu_lora_2021,
	title = {{LoRA}: {Low}-{Rank} {Adaptation} of {Large} {Language} {Models}},
	shorttitle = {{LoRA}},
	url = {http://arxiv.org/abs/2106.09685},
	doi = {10.48550/arXiv.2106.09685},
	publisher = {arXiv},
	author = {Hu, Edward J. and others},
	month = oct,
	year = {2021},
	note = {arXiv:2106.09685 [cs]},
}

@inproceedings{bai_bidirectional_2023,
	address = {Vancouver, BC, Canada},
	title = {Bidirectional {Copy}-{Paste} for {Semi}-{Supervised} {Medical} {Image} {Segmentation}},
	copyright = {https://doi.org/10.15223/policy-029},
	isbn = {979-8-3503-0129-8},
	url = {https://ieeexplore.ieee.org/document/10204177/},
	doi = {10.1109/CVPR52729.2023.01108},
	booktitle = {2023 {IEEE}/{CVF} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Bai, Yunhao and Chen, Duowen and Li, Qingli and Shen, Wei and Wang, Yan},
	month = jun,
	year = {2023},
	pages = {11514--11524},
}

@inproceedings{perazzi_learning_2017,
	address = {Honolulu, HI},
	title = {Learning {Video} {Object} {Segmentation} from {Static} {Images}},
	isbn = {978-1-5386-0457-1},
	url = {http://ieeexplore.ieee.org/document/8099855/},
	doi = {10.1109/CVPR.2017.372},
	booktitle = {2017 {IEEE} {Conference} on {Computer} {Vision} and {Pattern} {Recognition} ({CVPR})},
	publisher = {IEEE},
	author = {Perazzi, Federico and Khoreva, Anna and Benenson, Rodrigo and Schiele, Bernt and Sorkine-Hornung, Alexander},
	month = jul,
	year = {2017},
	pages = {3491--3500},
}

@article{ma_segment_2024,
	title = {Segment anything in medical images},
	volume = {15},
	copyright = {2024 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-024-44824-z},
	doi = {10.1038/s41467-024-44824-z},
	number = {1},
	urldate = {2025-12-09},
	journal = {Nature Communications},
	author = {Ma, Jun and others},
	month = jan,
	year = {2024},
	note = {Publisher: Nature Publishing Group},
	keywords = {Anatomy, Computer science, Machine learning, Medical imaging},
	pages = {654},
}

@article{isensee_nnu-net_2021,
	title = {{nnU}-{Net}: a self-configuring method for deep learning-based biomedical image segmentation},
	volume = {18},
	copyright = {2020 The Author(s), under exclusive licence to Springer Nature America, Inc.},
	issn = {1548-7105},
	shorttitle = {{nnU}-{Net}},
	url = {https://www.nature.com/articles/s41592-020-01008-z},
	doi = {10.1038/s41592-020-01008-z},
	number = {2},
	journal = {Nature Methods},
	publisher = {Nature Publishing Group},
	author = {Isensee, Fabian and Jaeger, Paul F. and Kohl, Simon A. A. and Petersen, Jens and Maier-Hein, Klaus H.},
	month = feb,
	year = {2021},
	keywords = {Image processing, Translational research},
	pages = {203--211},
}

@inproceedings{luo_efficient_2021,
	address = {Cham},
	title = {Efficient {Semi}-supervised {Gross} {Target} {Volume} of {Nasopharyngeal} {Carcinoma} {Segmentation} via {Uncertainty} {Rectified} {Pyramid} {Consistency}},
	isbn = {978-3-030-87196-3},
	doi = {10.1007/978-3-030-87196-3_30},
	booktitle = {Medical {Image} {Computing} and {Computer} {Assisted} {Intervention} – {MICCAI} 2021},
	publisher = {Springer International Publishing},
	author = {Luo, Xiangde and others},
	year = {2021},
	pages = {318--329},
}
