# models

@article{isensee2021nnunet,
  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}
}

@misc{kirillov2023sam,
      title={Segment Anything}, 
      author={Alexander Kirillov and Eric Mintun and Nikhila Ravi and Hanzi Mao and Chloe Rolland and Laura Gustafson and Tete Xiao and Spencer Whitehead and Alexander C. Berg and Wan-Yen Lo and Piotr Dollár and Ross Girshick},
      year={2023},
      eprint={2304.02643},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2304.02643}, 
}

@article{ravi2024sam2,
  title={SAM 2: Segment Anything in Images and Videos},
  author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph},
  journal={arXiv preprint arXiv:2408.00714},
  url={https://arxiv.org/abs/2408.00714},
  year={2024}
}

@article{jun2024medsam,
  title={Segment Anything in Medical Images},
  author={Ma, Jun and He, Yuting and Li, Feifei and Han, Lin and You, Chenyu and Wang, Bo},
  journal={Nature Communications},
  volume={15},
  pages={1--9},
  year={2024}
}

@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 Jiangand Hui Sun and Junjun He and Shaoting Zhang and Min Zhu and Yu Qiao},
  year={2023},
  eprint={2308.16184},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

@misc{wang2024sammed3d,
  title={SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images}, 
  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={2024},
  eprint={2310.15161},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2310.15161}, 
}

@misc{zhu2024medsam2,
  title={Medical SAM 2: Segment medical images as video via Segment Anything Model 2}, 
  author={Jiayuan Zhu and Yunli Qi and Junde Wu},
  year={2024},
  eprint={2408.00874},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2408.00874}, 
}

# datasets

@misc{Gut2021,
  author       = {Daniel Gut},
  title        = {X-ray images of the hip joints},
  year         = {2021},
  month        = {July},
  publisher    = {Mendeley Data},
  number       = {1},
}

@article{wasserthal2023totalsegmentator,
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}
}

@misc{liu2021ctpelvic1k,
  title={Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models}, 
  author={Pengbo Liu and Hu Han and Yuanqi Du and Heqin Zhu and Yinhao Li and Feng Gu and Honghu Xiao and Jun Li and Chunpeng Zhao and Li Xiao and Xinbao Wu and S. Kevin Zhou},
  year={2021},
  eprint={2012.08721},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2012.08721}, 
}

@article{verse2021,
title = {VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images},
journal = {Medical Image Analysis},
volume = {73},
pages = {102166},
year = {2021},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2021.102166},
url = {https://www.sciencedirect.com/science/article/pii/S1361841521002127},
author = {Anjany Sekuboyina and Malek E. Husseini and Amirhossein Bayat and Maximilian Löffler and Hans Liebl and Hongwei Li and Giles Tetteh and Jan Kukačka and Christian Payer and Darko Štern and Martin Urschler and Maodong Chen and Dalong Cheng and Nikolas Lessmann and Yujin Hu and Tianfu Wang and Dong Yang and Daguang Xu and Felix Ambellan and Tamaz Amiranashvili and Moritz Ehlke and Hans Lamecker and Sebastian Lehnert and Marilia Lirio and Nicolás Pérez de Olaguer and Heiko Ramm and Manish Sahu and Alexander Tack and Stefan Zachow and Tao Jiang and Xinjun Ma and Christoph Angerman and Xin Wang and Kevin Brown and Alexandre Kirszenberg and Élodie Puybareau and Di Chen and Yiwei Bai and Brandon H. Rapazzo and Timyoas Yeah and Amber Zhang and Shangliang Xu and Feng Hou and Zhiqiang He and Chan Zeng and Zheng Xiangshang and Xu Liming and Tucker J. Netherton and Raymond P. Mumme and Laurence E. Court and Zixun Huang and Chenhang He and Li-Wen Wang and Sai Ho Ling and Lê Duy Huỳnh and Nicolas Boutry and Roman Jakubicek and Jiri Chmelik and Supriti Mulay and Mohanasankar Sivaprakasam and Johannes C. Paetzold and Suprosanna Shit and Ivan Ezhov and Benedikt Wiestler and Ben Glocker and Alexander Valentinitsch and Markus Rempfler and Björn H. Menze and Jan S. Kirschke},
keywords = {Spine, Vertebrae, Segmentation, Labelling},
}

@article{ye2023sammed2d_dataset,
  title={SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks},
  author={Ye, Jin and Cheng, Junlong and Chen, Jianpin and Deng, Zhongying and Li, Tianbin and Wang, Haoyu and Su, Yanzhou and Huang, Ziyan and Chen, Jilong and Jiang, Lei and others},
  journal={arXiv preprint arXiv:2311.11969},
  year={2023}
}

# sam evaluation study and related work

@article{MAZUROWSKI2023eval,
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},
keywords = {Segmentation, Foundation models, Deep learning},
}

@article{ZHANG2024evalfirst,
title = {Segment anything model for medical image segmentation: Current applications and future directions},
journal = {Computers in Biology and Medicine},
volume = {171},
pages = {108238},
year = {2024},
issn = {0010-4825},
doi = {https://doi.org/10.1016/j.compbiomed.2024.108238},
url = {https://www.sciencedirect.com/science/article/pii/S0010482524003226},
author = {Yichi Zhang and Zhenrong Shen and Rushi Jiao},
}

@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},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2305.00035}, 
}

@misc{he2023eval,
  title={Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets}, 
  author={Sheng He and Rina Bao and Jingpeng Li and Jeffrey Stout and Atle Bjornerud and P. Ellen Grant and Yangming Ou},
  year={2023},
  eprint={2304.09324},
  archivePrefix={arXiv},
  primaryClass={eess.IV},
  url={https://arxiv.org/abs/2304.09324}, 
}

@INPROCEEDINGS{mattjie2023eval,
  author={Mattjie, Christian and De Moura, Luis Vinicius and Ravazio, Rafaela and Kupssinskü, Lucas and Parraga, Otávio and Delucis, Marcelo Mussi and Barros, Rodrigo C.},
  booktitle={2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE)}, 
  title={Zero-Shot Performance of the Segment Anything Model (SAM) in 2D Medical Imaging: A Comprehensive Evaluation and Practical Guidelines}, 
  year={2023},
  volume={},
  number={},
  pages={108-112},
  keywords={Image segmentation;Adaptation models;Ultrasonic imaging;Zero-shot learning;Biological system modeling;Biomedical imaging;Guidelines;Medical Imaging;Segmentation;Segment Anything Model;Zero-shot Learning;Deep Learning},
  doi={10.1109/BIBE60311.2023.00025}
}

@misc{dong2024eval,
  title={Segment anything model 2: an application to 2D and 3D medical images}, 
  author={Haoyu Dong and Hanxue Gu and Yaqian Chen and Jichen Yang and Yuwen Chen and Maciej A. Mazurowski},
  year={2024},
  eprint={2408.00756},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2408.00756}, 
}

@misc{zhang2024evalsecond,
      title={Unleashing the Potential of SAM2 for Biomedical Images and Videos: A Survey}, 
      author={Yichi Zhang and Zhenrong Shen},
      year={2024},
      eprint={2408.12889},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2408.12889}, 
}

@misc{roy2023sammd,
  title={SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model}, 
  author={Saikat Roy and Tassilo Wald and Gregor Koehler and Maximilian R. Rokuss and Nico Disch and Julius Holzschuh and David Zimmerer and Klaus H. Maier-Hein},
  year={2023},
  eprint={2304.05396},
  archivePrefix={arXiv},
  primaryClass={eess.IV},
  url={https://arxiv.org/abs/2304.05396}, 
}

@article{HUANG2024eval,
title = {Segment anything model for medical images?},
journal = {Medical Image Analysis},
volume = {92},
pages = {103061},
year = {2024},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2023.103061},
url = {https://www.sciencedirect.com/science/article/pii/S1361841523003213},
author = {Yuhao Huang and Xin Yang and Lian Liu and Han Zhou and Ao Chang and Xinrui Zhou and Rusi Chen and Junxuan Yu and Jiongquan Chen and Chaoyu Chen and Sijing Liu and Haozhe Chi and Xindi Hu and Kejuan Yue and Lei Li and Vicente Grau and Deng-Ping Fan and Fajin Dong and Dong Ni},
}

@misc{yu2024eval,
  title={SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation}, 
  author={Jieming Yu and An Wang and Wenzhen Dong and Mengya Xu and Mobarakol Islam and Jie Wang and Long Bai and Hongliang Ren},
  year={2024},
  eprint={2408.04593},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2408.04593}, 
}

@misc{he2024evalct,
  title={A Short Review and Evaluation of SAM2's Performance in 3D CT Image Segmentation}, 
  author={Yufan He and Pengfei Guo and Yucheng Tang and Andriy Myronenko and Vishwesh Nath and Ziyue Xu and Dong Yang and Can Zhao and Daguang Xu and Wenqi Li},
  year={2024},
  eprint={2408.11210},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2408.11210}, 
}

@misc{sengupta2024eval,
  title={Is SAM 2 Better than SAM in Medical Image Segmentation?}, 
  author={Sourya Sengupta and Satrajit Chakrabarty and Ravi Soni},
  year={2024},
  eprint={2408.04212},
  archivePrefix={arXiv},
  primaryClass={eess.IV},
  url={https://arxiv.org/abs/2408.04212}, 
}

@misc{shen2024eval,
  title={Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation}, 
  author={Yiqing Shen and Hao Ding and Xinyuan Shao and Mathias Unberath},
  year={2024},
  eprint={2408.04098},
  archivePrefix={arXiv},
  primaryClass={eess.IV},
  url={https://arxiv.org/abs/2408.04098}, 
}

# tools

@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
    Anatomical Structures: Significantly Improved Efficiency and Reliability},
  journal = {Neuroimage},
  year = {2006},
  volume = {31},
  number = {3},
  pages = {1116--1128},
}

@article{dobbe2014,
    title = {Evaluation of a {CT}-based technique to measure the transfer accuracy of a virtually planned osteotomy},
    journal = {Medical Engineering \& Physics},
    volume = {36},
    number = {8},
    pages = {1081-1087},
    year = {2014},
    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}
}

@article{jia2024seg,
  title={seg-metrics: a Python package to compute segmentation metrics},
  author={Jia, Jingnan and Staring, Marius and Stoel, Berend C},
  journal={medRxiv},
  pages={2024--02},
  year={2024},
  publisher={Cold Spring Harbor Laboratory Press}
}

@online{plotly, author = {Plotly Technologies Inc.}, title = {Collaborative data science}, publisher = {Plotly Technologies Inc.}, address = {Montreal, QC}, year = {2015}, url = {https://plot.ly} }

