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@misc{Hinton:arXiv:2015:Distilling,
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@article{mazurowski2023,
title = {Segment anything model for medical image analysis: An experimental study},
journal = {Medical Image Analysis},
volume = {89},
pages = {102918},
year = {2023},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2023.102918},
url = {https://www.sciencedirect.com/science/article/pii/S1361841523001780},
author = {Maciej A. Mazurowski and Haoyu Dong and Hanxue Gu and Jichen Yang and Nicholas Konz and Yixin Zhang},
}

@ARTICLE{itk_snap,
  author = {Paul A. Yushkevich and Joseph Piven and Cody Hazlett, Heather and
    Gimpel Smith, Rachel and Sean Ho and James C. Gee and Guido Gerig},
  title = {User-Guided {3D} Active Contour Segmentation of
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}

@article{dobbe2014,
    title = {Evaluation of a {CT}-based technique to measure the transfer accuracy of a virtually planned osteotomy},
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    issn = {1350-4533},
    author = {J.G.G. Dobbe and A.J. Kievit and M.U. Schafroth and L. Blankevoort and G.J. Streekstra},
    keywords = {Corrective osteotomy, Patient specific instrumentation, Cutting guide, Virtual planning, TKA}
}
%doi = {https://doi.org/10.1016/j.medengphy.2014.05.012},
%url = {https://www.sciencedirect.com/science/article/pii/S1350453314001271},

@article{wasserthal2023,
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},
doi = {10.1148/ryai.230024},
URL = {https://doi.org/10.1148/ryai.230024}
}

@article{isensee2021,
  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{kirillov2023sam,
  title={Segment anything},
  author={Kirillov, Alexander and Mintun, Eric and Ravi, Nikhila and Mao, Hanzi and Rolland, Chloe and Gustafson, Laura and Xiao, Tete and Whitehead, Spencer and Berg, Alexander C and Lo, Wan-Yen and others},
  journal={arXiv preprint arXiv:2304.02643},
  year={2023}
}

@article{huang2023sam,
  title={Segment anything model for medical images?},
  author={Huang, Yuhao and Yang, Xin and Liu, Lian and Zhou, Han and Chang, Ao and Zhou, Xinrui and Chen, Rusi and Yu, Junxuan and Chen, Jiongquan and Chen, Chaoyu and others},
  journal={Medical Image Analysis},
  pages={103061},
  year={2023},
  publisher={Elsevier}
}

@article{he2023eval,
  title={Accuracy of segment-anything model ({sam}) in medical image segmentation tasks},
  author={He, Sheng and Bao, Rina and Li, Jingpeng and Grant, P Ellen and Ou, Yangming},
  journal={arXiv preprint arXiv:2304.09324},
  year={2023}
}

@misc{wu2023medsa,
  title={{Medical SAM Adapter}: Adapting Segment Anything Model for Medical Image Segmentation}, 
  author={Junde Wu and Wei Ji and Yuanpei Liu and Huazhu Fu and Min Xu and Yanwu Xu and Yueming Jin},
  year={2023},
  eprint={2304.12620},
  archivePrefix={arXiv},
  url={
https://doi.org/10.48550/arXiv.2304.12620},
  primaryClass={cs.CV}
}

@misc{cheng2023sammed2d,
  title={{SAM-Med2D}}, 
  author={Junlong Cheng and Jin Ye and Zhongying Deng and Jianpin Chen and Tianbin Li and Haoyu Wang and Yanzhou Su and Ziyan Huang and Jilong Chen and Lei Jiang and Hui Sun and Junjun He and Shaoting Zhang and Min Zhu and Yu Qiao},
  year={2023},
  eprint={2308.16184},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2308.16184},
  primaryClass={cs.CV}
}

@misc{ma2023medsam,
  title={Segment Anything in Medical Images}, 
  author={Jun Ma and Yuting He and Feifei Li and Lin Han and Chenyu You and Bo Wang},
  year={2023},
  eprint={2304.12306},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2304.12306},
  primaryClass={eess.IV}
}

@misc{cheng2023eval,
  title={{SAM} on Medical Images: A Comprehensive Study on Three Prompt Modes}, 
  author={Dongjie Cheng and Ziyuan Qin and Zekun Jiang and Shaoting Zhang and Qicheng Lao and Kang Li},
  year={2023},
  eprint={2305.00035},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2305.00035},
  primaryClass={cs.CV}
}

@misc{hu2023autosam,
  title={How to Efficiently Adapt Large Segmentation Model({SAM}) to Medical Images}, 
  author={Xinrong Hu and Xiaowei Xu and Yiyu Shi},
  year={2023},
  eprint={2306.13731},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

@misc{lei2023medlsam,
  title={{MedLSAM}: Localize and Segment Anything Model for {3D CT} Images}, 
  author={Wenhui Lei and Xu Wei and Xiaofan Zhang and Kang Li and Shaoting Zhang},
  year={2023},
  eprint={2306.14752},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2306.14752},
  primaryClass={cs.CV}
}

@misc{li2023autoprompting,
  title={Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation}, 
  author={Chengyin Li and Prashant Khanduri and Yao Qiang and Rafi Ibn Sultan and Indrin Chetty and Dongxiao Zhu},
  year={2023},
  eprint={2308.14936},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2308.14936},
  primaryClass={cs.CV}
}

@misc{zhang2023semisam,
  title={SemiSAM: Exploring SAM for Enhancing Semi-Supervised Medical Image Segmentation with Extremely Limited Annotations}, 
  author={Yichi Zhang and Yuan Cheng and Yuan Qi},
  year={2023},
  eprint={2312.06316},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

@InProceedings{xie2024fewshot,
    author    = {Xie, Weiyi and Willems, Nathalie and Patil, Shubham and Li, Yang and Kumar, Mayank},
    title     = {{SAM} Fewshot Finetuning for Anatomical Segmentation in Medical Images},
    booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
    month     = {January},
    year      = {2024},
    pages     = {3253-3261}
}

@misc{wang2023sammed3d,
  title={{SAM-Med3D}}, 
  author={Haoyu Wang and Sizheng Guo and Jin Ye and Zhongying Deng and Junlong Cheng and Tianbin Li and Jianpin Chen and Yanzhou Su and Ziyan Huang and Yiqing Shen and Bin Fu and Shaoting Zhang and Junjun He and Yu Qiao},
  year={2023},
  eprint={2310.15161},
  url={https://doi.org/10.48550/arXiv.2308.16184},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

@misc{xu2023eviprompt,
  title={{EviPrompt}: A Training-Free Evidential Prompt Generation Method for Segment Anything Model in Medical Images}, 
  author={Yinsong Xu and Jiaqi Tang and Aidong Men and Qingchao Chen},
  year={2023},
  eprint={2311.06400},
  archivePrefix={arXiv},
  url={https://doi.org/10.48550/arXiv.2311.06400},
  primaryClass={cs.CV}
}

@article{lindgrenbelal2019,
    title = {Deep learning for segmentation of 49 selected bones in {CT} scans: First step in automated {PET}/{CT}-based {3D} quantification of skeletal metastases},
    journal = {European Journal of Radiology},
    volume = {113},
    pages = {89-95},
    year = {2019},
    issn = {0720-048X},
    doi = {https://doi.org/10.1016/j.ejrad.2019.01.028},
    url = {https://www.sciencedirect.com/science/article/pii/S0720048X1930035X},
    author = {Sarah {Lindgren Belal} and May Sadik and Reza Kaboteh and Olof Enqvist and Johannes Ulén and Mads H. Poulsen and Jane Simonsen and Poul F. Høilund-Carlsen and Lars Edenbrandt and Elin Tr{ä}g{å}rdh},
    keywords = {PET/CT, Artificial intelligence, Bone, Metastases, Prostate cancer}
}

@article{deng2022,
  title={A deep learning-based approach to automatic proximal femur segmentation in quantitative {CT} images},
  author={Deng, Yu and Wang, Ling and Zhao, Chen and Tang, Shaojie and Cheng, Xiaoguang and Deng, Hong-Wen and Zhou, Weihua},
  journal={Medical \& biological engineering \& computing},
  volume={60},
  number={5},
  pages={1417--1429},
  year={2022},
  publisher={Springer}
}

@article{bonaldi2023msk,
  title={Deep learning-based medical images segmentation of musculoskeletal anatomical structures: a survey of bottlenecks and strategies},
  author={Bonaldi, Lorenza and Pretto, Andrea and Pirri, Carmelo and Uccheddu, Francesca and Fontanella, Chiara Giulia and Stecco, Carla},
  journal={Bioengineering},
  volume={10},
  number={2},
  pages={137},
  year={2023},
  publisher={MDPI}
}

@inproceedings{magg2024,
    author = {Magg, Caroline and ter Wee, Maaike A. and Buijs, George S. and Kievit, Arthur J. and Krap, Dennis A. and Dobbe, Johannes G.G. and Streekstra, Geert J. and Blankevoort, Leendert and S\'anchez, Clara I.},
    title = {Towards automation in non-invasive measurement of knee implant displacement} ,
    booktitle = {SPIE Medical Imaging},
    year = {2024}
}