% Citations for PEFT-SAM Paper

@InProceedings{Kirrilov:arXiv:2023:SAM,
  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 Dollar, Piotr and Girshick, Ross},
  title = {Segment Anything},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  month = {October},
  year = {2023},
  pages = {4015-4026},
  url = {https://openaccess.thecvf.com/content/ICCV2023/html/Kirillov_Segment_Anything_ICCV_2023_paper.html},
}

@inproceedings{
    hu:2021:lora,
    title={Lo{RA}: Low-Rank Adaptation of Large Language Models},
    author={Edward J Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen},
    booktitle={International Conference on Learning Representations},
    year={2022},
    url={https://openreview.net/forum?id=nZeVKeeFYf9}
}

@article{Archit:arXiv:2023:MicroSAM,
  title = {Segment Anything for Microscopy},
  volume = {22},
  ISSN = {1548-7105},
  url = {http://doi.org/10.1038/s41592-024-02580-4},
  DOI = {10.1038/s41592-024-02580-4},
  number = {3},
  journal = {Nature Methods},
  publisher = {Springer Science and Business Media LLC},
  author = {Archit,  Anwai and Freckmann,  Luca and Nair,  Sushmita and Khalid,  Nabeel and Hilt,  Paul and Rajashekar,  Vikas and Freitag,  Marei and Teuber,  Carolin and Buckley,  Genevieve and von Haaren,  Sebastian and Gupta,  Sagnik and Dengel,  Andreas and Ahmed,  Sheraz and Pape,  Constantin},
  year = {2025},
  month = feb,
  pages = {579–591}
}

@article{dosovitskiy_arxiv:2021:vit,
  title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and  Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and Uszkoreit, Jakob and Houlsby, Neil},
  journal={ICLR},
  year={2021},
  url={https://openreview.net/forum?id=YicbFdNTTy}
}

@article{Edlund:nature:2021:LIVECell,
  author = {Edlund, Christoffer and Jackson, Timothy R. and Khalid, Nabeel and Bevan, Nicola and Dale, Timothy and Dengel, Andreas and Ahmed, Sheraz and Trygg, Johan and Sjögren, Rickard},
  title = {LIVECell—A large-scale dataset for label-free live cell segmentation},
  journal = {Nature Methods},
  year = {2021},
  volume = {18},
  number = {9},
  pages = {1038--1045},
  doi = {10.1038/s41592-021-01249-6},
  url = {https://doi.org/10.1038/s41592-021-01249-6},
  sn = {1548-7105},
}

@article{Pape:BioEssays:2021:CovidIF,
    author = {Pape, Constantin and Remme, Roman and Wolny, Adrian and Olberg, Sylvia and Wolf, Steffen and Cerrone, Lorenzo and Cortese, Mirko and Klaus, Severina and Lucic, Bojana and Ullrich, Stephanie and Anders-Össwein, Maria and Wolf, Stefanie and Cerikan, Berati and Neufeldt, Christopher J. and Ganter, Markus and Schnitzler, Paul and Merle, Uta and Lusic, Marina and Boulant, Steeve and Stanifer, Megan and Bartenschlager, Ralf and Hamprecht, Fred A. and Kreshuk, Anna and Tischer, Christian and Kräusslich, Hans-Georg and Müller, Barbara and Laketa, Vibor},
    title = {Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera},
    journal = {BioEssays},
    volume = {43},
    number = {3},
    pages = {2000257},
    keywords = {antibody, immunofluorescence, machine learning image analysis, quantitative microscopy, SARS-CoV-2, serological test},
    url = {https://doi.org/10.1002/bies.202000257},
    eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/bies.202000257},
    year = {2021}
}

@article{Ouyang:nm:2019:hpa,
  author    = {Wei Ouyang and Casper F. Winsnes and Martin Hjelmare and Anthony J. Cesnik and Lovisa Åkesson and Hao Xu and Devin P. Sullivan and Shubin Dai and Jun Lan and Jinmo Park and Shaikat M. Galib and Christof Henkel and Kevin Hwang and Dmytro Poplavskiy and Bojan Tunguz and Russel D. Wolfinger and Yinzheng Gu and Chuanpeng Li and Jinbin Xie and Dmitry Buslov and Sergei Fironov and Alexander Kiselev and Dmytro Panchenko and Xuan Cao and Runmin Wei and Yuanhao Wu and Xun Zhu and Kuan-Lun Tseng and Zhifeng Gao and Cheng Ju and Xiaohan Yi and Hongdong Zheng and Constantin Kappel and Emma Lundberg},
  title     = {Analysis of the Human Protein Atlas Image Classification competition},
  journal   = {Nature Methods},
  year      = {2019},
  volume    = {16},
  number    = {12},
  pages     = {1254--1261},
  doi       = {10.1038/s41592-019-0658-6},
  url       = {https://doi.org/10.1038/s41592-019-0658-6},
  issn      = {1548-7105},
}

@article{Vijayan:dev:2024:gonuclear,
    author = {Vijayan, Athul and Mody, Tejasvinee Atul and Yu, Qin and Wolny, Adrian and Cerrone, Lorenzo and Strauss, Soeren and Tsiantis, Miltos and Smith, Richard S. and Hamprecht, Fred A. and Kreshuk, Anna and Schneitz, Kay},
    title = {A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context},
    journal = {Development},
    volume = {151},
    number = {14},
    pages = {dev202800},
    year = {2024},
    month = {07},
    issn = {0950-1991},
    doi = {10.1242/dev.202800},
    url = {https://doi.org/10.1242/dev.202800},
}

@article{Lefferts:CB:2024:orgasegment,
  author    = {Juliet W. Lefferts and Suzanne Kroes and Matthew B. Smith and Paul J. Niemöller and Natascha D. A. Nieuwenhuijze and Heleen N. Sonneveld van Kooten and Cornelis K. van der Ent and Jeffrey M. Beekman and Sam F. B. van Beuningen},
  title     = {OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion},
  journal   = {Communications Biology},
  year      = {2024},
  volume    = {7},
  number    = {1},
  pages     = {319},
  doi       = {10.1038/s42003-024-05966-4},
  url       = {https://doi.org/10.1038/s42003-024-05966-4},
  issn      = {2399-3642},
}

@article{Conrad:cs:2023:mitolab,
  author    = {Ryan Conrad and Kedar Narayan},
  title     = {Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model trained on a diverse dataset},
  journal   = {Cell Systems},
  year      = {2023},
  volume    = {14},
  number    = {1},
  pages     = {58--71.e5},
  doi       = {10.1016/j.cels.2022.12.006},
  url       = {https://doi.org/10.1016/j.cels.2022.12.006},
  issn      = {2405-4712},
  publisher = {Elsevier},
}

@article{Vergara:cell:2021:platynereis,
  author    = {Hernando M. Vergara and Constantin Pape and Kimberly I. Meechan and Valentyna Zinchenko and Christel Genoud and Adrian A. Wanner and Kevin Nzumbi Mutemi and Benjamin Titze and Rachel M. Templin and Paola Y. Bertucci and Oleg Simakov and Wiebke Dürichen and Pedro Machado and Emily L. Savage and Lothar Schermelleh and Yannick Schwab and Rainer W. Friedrich and Anna Kreshuk and Christian Tischer and Detlev Arendt},
  title     = {Whole-body integration of gene expression and single-cell morphology},
  journal   = {Cell},
  year      = {2021},
  volume    = {184},
  number    = {18},
  pages     = {4819--4837.e22},
  doi       = {10.1016/j.cell.2021.07.017},
  url       = {https://doi.org/10.1016/j.cell.2021.07.017},
  issn      = {0092-8674},
  publisher = {Elsevier},
}

@article{gu:arxiv:2024:bestmedicalmodel,
  title = {How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model},
  volume = {3},
  ISSN = {2766-905X},
  url = {http://doi.org/10.59275/j.melba.2025-86a6},
  DOI = {10.59275/j.melba.2025-86a6},
  number = {May 2025},
  journal = {Machine Learning for Biomedical Imaging},
  publisher = {Machine Learning for Biomedical Imaging},
  author = {Gu,  Hanxue and Dong,  Haoyu and Yang,  Jichen and Mazurowski,  Maciej A.},
  year = {2025},
  month = may,
  pages = {88–120}
}

@inproceedings{dutt:openreview:2024:parameterefficient,
    title={Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity},
    author={Raman Dutt and Linus Ericsson and Pedro Sanchez and Sotirios A. Tsaftaris and Timothy Hospedales},
    booktitle={Medical Imaging with Deep Learning},
    year={2024},
    url={https://openreview.net/forum?id=LVRhXa0q5r}
}

@inproceedings{chen:arxiv:2022:adaptformer,
     author = {Chen, Shoufa and GE, Chongjian and Tong, Zhan and Wang, Jiangliu and Song, Yibing and Wang, Jue and Luo, Ping},
     booktitle = {Advances in Neural Information Processing Systems},
     editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
     pages = {16664--16678},
     publisher = {Curran Associates, Inc.},
     title = {AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition},
     url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/69e2f49ab0837b71b0e0cb7c555990f8-Paper-Conference.pdf},
     volume = {35},
     year = {2022}
}

@InProceedings{lian:2023:arxiv:ssf,
  title={Scaling \& Shifting Your Features: A New Baseline for Efficient Model Tuning},
  author={Lian, Dongze and Zhou, Daquan and Feng, Jiashi and Wang, Xinchao},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  year={2022},
  url={https://papers.neurips.cc/paper_files/paper/2022/file/00bb4e415ef117f2dee2fc3b778d806d-Paper-Conference.pdf},
}

@article{jie:arxiv:2023:fact,
  title = {FacT: Factor-Tuning for Lightweight Adaptation on Vision Transformer},
  volume = {37},
  ISSN = {2159-5399},
  url = {http://doi.org/10.1609/aaai.v37i1.25187},
  DOI = {10.1609/aaai.v37i1.25187},
  number = {1},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
  author = {Jie,  Shibo and Deng,  Zhi-Hong},
  year = {2023},
  month = jun,
  pages = {1060–1068}
}

@article{Caicedo:2019:dsb,
  author    = {Caicedo, Juan C. and Goodman, Allen and Karhohs, Kyle W. and Cimini, Beth A. and Ackerman, Jeanelle and Haghighi, Marzieh and Heng, CherKeng and Becker, Tim and Doan, Minh and McQuin, Claire and Rohban, Mohammad and Singh, Shantanu and Carpenter, Anne E.},
  title     = {Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl},
  journal   = {Nature Methods},
  year      = {2019},
  volume    = {16},
  number    = {12},
  pages     = {1247--1253},
  doi       = {10.1038/s41592-019-0612-7},
  url       = {https://doi.org/10.1038/s41592-019-0612-7},
  issn      = {1548-7105}
}

@misc{zhou:2024:cellseg1,
  title={CellSeg1: Robust Cell Segmentation with One Training Image}, 
  author={Peilin Zhou and Bo Du and Yongchao Xu},
  year={2024},
  eprint={2412.01410},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://doi.org/10.48550/arXiv.2412.01410}, 
}

@article{Pachitariu:2022:cellpose2,
  author = {Pachitariu, Marius and Stringer, Carsen},
  title = {Cellpose 2.0: how to train your own model},
  journal = {Nature Methods},
  year = {2022},
  volume = {19},
  number = {12},
  pages = {1634--1641},
  month = dec,
  issn = {1548-7105},
  doi = {10.1038/s41592-022-01663-4},
  url = {https://doi.org/10.1038/s41592-022-01663-4}
}

@inbook{Weigert:2022:stardist,
  title = {Cell Detection with Star-Convex Polygons},
  ISBN = {9783030009342},
  ISSN = {1611-3349},
  url = {http://doi.org/10.1007/978-3-030-00934-2_30},
  DOI = {10.1007/978-3-030-00934-2_30},
  booktitle = {Medical Image Computing and Computer Assisted Intervention – MICCAI 2018},
  publisher = {Springer International Publishing},
  author = {Schmidt,  Uwe and Weigert,  Martin and Broaddus,  Coleman and Myers,  Gene},
  year = {2018},
  pages = {265–273}
}

@article{MaierHein:2021:nnunet,
  title = {nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation},
  volume = {18},
  ISSN = {1548-7105},
  url = {http://doi.org/10.1038/s41592-020-01008-z},
  DOI = {10.1038/s41592-020-01008-z},
  number = {2},
  journal = {Nature Methods},
  publisher = {Springer Science and Business Media LLC},
  author = {Isensee,  Fabian and Jaeger,  Paul F. and Kohl,  Simon A. A. and Petersen,  Jens and Maier-Hein,  Klaus H.},
  year = {2020},
  month = dec,
  pages = {203–211}
}

@inproceedings{zou:2023:seem,
    author = {Zou, Xueyan and Yang, Jianwei and Zhang, Hao and Li, Feng and Li, Linjie and Wang, Jianfeng and Wang, Lijuan and Gao, Jianfeng and Lee, Yong Jae},
    title = {Segment everything everywhere all at once},
    year = {2023},
    publisher = {Curran Associates Inc.},
    address = {Red Hook, NY, USA},
    booktitle = {Proceedings of the 37th International Conference on Neural Information Processing Systems},
    articleno = {868},
    numpages = {14},
    location = {New Orleans, LA, USA},
    series = {NIPS '23},
    url={https://openreview.net/forum?id=UHBrWeFWlL}
}

@misc{pu:2023:empiricalanalysisstrengthsweaknesses,
  title={Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs}, 
  author={George Pu and Anirudh Jain and Jihan Yin and Russell Kaplan},
  year={2023},
  booktitle={ICLR 2023 Workshop ME-FoMo},
  url={https://openreview.net/forum?id=HB7zDQ4mvX}, 
}

@misc{xu:2023:parameterefficientfinetuningmethodspretrained,
  title={Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment}, 
  author={Lingling Xu and Haoran Xie and Si-Zhao Joe Qin and Xiaohui Tao and Fu Lee Wang},
  year={2023},
  eprint={2312.12148},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://doi.org/10.48550/arXiv.2312.12148}, 
}

@misc{balne:2024:parameterefficientfinetuning,
  title={Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications}, 
  author={Charith Chandra Sai Balne and Sreyoshi Bhaduri and Tamoghna Roy and Vinija Jain and Aman Chadha},
  year={2024},
  eprint={2404.13506},
  archivePrefix={arXiv},
  primaryClass={cs.LG},
  url={https://doi.org/10.48550/arXiv.2404.13506}, 
}

@misc{zhang2023customizedsegmentmodelmedical,
  title={Customized Segment Anything Model for Medical Image Segmentation}, 
  author={Kaidong Zhang and Dong Liu},
  year={2023},
  eprint={2304.13785},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://doi.org/10.48550/arXiv.2304.13785}, 
}

@inbook{wei:2024:imedsam,
  title = {I-MedSAM: Implicit Medical Image Segmentation with Segment Anything},
  ISBN = {9783031726842},
  ISSN = {1611-3349},
  url = {http://doi.org/10.1007/978-3-031-72684-2_6},
  DOI = {10.1007/978-3-031-72684-2_6},
  booktitle = {Computer Vision – ECCV 2024},
  publisher = {Springer Nature Switzerland},
  author = {Wei,  Xiaobao and Cao,  Jiajun and Jin,  Yizhu and Lu,  Ming and Wang,  Guangyu and Zhang,  Shanghang},
  year = {2024},
  month = nov,
  pages = {90–107}
}

@misc{xin2024parameterefficientfinetuningpretrainedvision,
  title={Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models: A Survey}, 
  author={Yi Xin and Siqi Luo and Haodi Zhou and Junlong Du and Xiaohong Liu and Yue Fan and Qing Li and Yuntao Du},
  year={2024},
  eprint={2402.02242},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://doi.org/10.48550/arXiv.2402.02242}, 
}

@inproceedings{zahweh2023empiricalstudypefttechniques,
  series = {ECRS 2023},
  title = {Empirical Study of PEFT Techniques for Winter-Wheat Segmentation},
  url = {http://doi.org/10.3390/ECRS2023-15833},
  DOI = {10.3390/ecrs2023-15833},
  booktitle = {ECRS 2023},
  publisher = {MDPI},
  author = {Zahweh,  Mohamad Hasan and Nasrallah,  Hasan and Shukor,  Mustafa and Faour,  Ghaleb and Ghandour,  Ali J.},
  year = {2023},
  month = nov,
  pages = {50},
  collection = {ECRS 2023}
}

@inproceedings{benzaken:2021:bitfit,
  title = {BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models},
  url = {http://doi.org/10.18653/v1/2022.acl-short.1},
  DOI = {10.18653/v1/2022.acl-short.1},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  publisher = {Association for Computational Linguistics},
  author = {Ben Zaken,  Elad and Goldberg,  Yoav and Ravfogel,  Shauli},
  year = {2022}
}

@inbook{touvron:2022:attntune,
  title = {Three Things Everyone Should Know About Vision Transformers},
  ISBN = {9783031200533},
  ISSN = {1611-3349},
  url = {http://doi.org/10.1007/978-3-031-20053-3_29},
  DOI = {10.1007/978-3-031-20053-3_29},
  booktitle = {Computer Vision – ECCV 2022},
  publisher = {Springer Nature Switzerland},
  author = {Touvron,  Hugo and Cord,  Matthieu and El-Nouby,  Alaaeldin and Verbeek,  Jakob and Jégou,  Hervé},
  year = {2022},
  pages = {497–515}
}

@article{basu:2023:layernormtune,
  title = {Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning},
  volume = {38},
  ISSN = {2159-5399},
  url = {http://doi.org/10.1609/aaai.v38i10.28978},
  DOI = {10.1609/aaai.v38i10.28978},
  number = {10},
  journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
  publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
  author = {Basu,  Samyadeep and Hu,  Shell and Massiceti,  Daniela and Feizi,  Soheil},
  year = {2024},
  month = mar,
  pages = {11024–11031}
}

@inproceedings{cai:2021:biastune,
    author = {Cai, Han and Gan, Chuang and Massachusetts Institute of Technology, Ligeng Zhu and Massachusetts Institute of Technology, Song Han},
    title = {TinyTL: reduce memory, not parameters for efficient on-device learning},
    year = {2020},
    isbn = {9781713829546},
    publisher = {Curran Associates Inc.},
    address = {Red Hook, NY, USA},
    booktitle = {Proceedings of the 34th International Conference on Neural Information Processing Systems},
    articleno = {947},
    numpages = {13},
    location = {Vancouver, BC, Canada},
    series = {NIPS '20},
    url = {https://proceedings.neurips.cc/paper/2020/file/81f7acabd411274fcf65ce2070ed568a-Paper.pdf}
}

@misc{frankle:2021:batchnormtune,
  title={Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs}, 
  author={Jonathan Frankle and David J. Schwab and Ari S. Morcos},
  year={2021},
  booktitle={ICLR},
  url={https://openreview.net/forum?id=vYeQQ29Tbvx}, 
}

@misc{dettmers:2023:qlora,
  title={QLoRA: Efficient Finetuning of Quantized LLMs}, 
  author={Tim Dettmers and Artidoro Pagnoni and Ari Holtzman and Luke Zettlemoyer},
  year={2023},
  booktitle={NeurIPS},
  url={https://openreview.net/forum?id=OUIFPHEgJU}, 
}

@InProceedings{hatamizadeh:2021:unetr,
    author    = {Hatamizadeh, Ali and Tang, Yucheng and Nath, Vishwesh and Yang, Dong and Myronenko, Andriy and Landman, Bennett and Roth, Holger R. and Xu, Daguang},
    title     = {UNETR: Transformers for 3D Medical Image Segmentation},
    booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
    month     = {January},
    year      = {2022},
    pages     = {574-584},
    url = {https://openaccess.thecvf.com/content/WACV2022/papers/Hatamizadeh_UNETR_Transformers_for_3D_Medical_Image_Segmentation_WACV_2022_paper.pdf}
}

% PEFT: https://arxiv.org/html/2403.14608v1

@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{wasserthal2023totalsegmentator,
  title={TotalSegmentator: robust segmentation of 104 anatomic structures in CT images},
  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 others},
  journal={Radiology: Artificial Intelligence},
  volume={5},
  number={5},
  year={2023},
  publisher={Radiological Society of North America},
  url={https://doi.org/10.1148/ryai.230024}
}

@article{israel2024foundation,
  title={A foundation model for cell segmentation},
  author={Israel, Uriah and Marks, Markus and Dilip, Rohit and Li, Qilin and Yu, Changhua and Laubscher, Emily and Li, Shenyi and Schwartz, Morgan and Pradhan, Elora and Ates, Ada and others},
  journal={bioRxiv},
  pages={2023--11},
  year={2024},
  url={https://doi.org/10.1101/2023.11.17.567630}
}

% https://arxiv.org/abs/2501.11734
@misc{archit2025medico,
  title={MedicoSAM: Towards foundation models for medical image segmentation},
  author={Archit, Anwai and Freckmann, Luca and Pape, Constantin},
  year={2025},
  eprint={2501.11734},
  archivePrefix={arXiv},
  primaryClass={eess.IV},
  url={https://doi.org/10.48550/arXiv.2501.11734}, 
}

@article{ma2024segment,
  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},
  number={1},
  pages={654},
  year={2024},
  publisher={Nature Publishing Group UK London},
  url={https://doi.org/10.1038/s41467-024-44824-z}
}

@article{zhao2024foundation,
  title={A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities},
  author={Zhao, Theodore and Gu, Yu and Yang, Jianwei and Usuyama, Naoto and Lee, Ho Hin and Kiblawi, Sid and Naumann, Tristan and Gao, Jianfeng and Crabtree, Angela and Abel, Jacob and others},
  journal={Nature methods},
  pages={1--11},
  year={2024},
  publisher={Nature Publishing Group US New York},
  url={https://doi.org/10.1038/s41592-024-02499-w}
}

@article{psfhs,
  title = {PSFHS: Intrapartum ultrasound image dataset for AI-based segmentation of pubic symphysis and fetal head},
  volume = {11},
  ISSN = {2052-4463},
  url = {http://doi.org/10.1038/s41597-024-03266-4},
  DOI = {10.1038/s41597-024-03266-4},
  number = {1},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Chen,  Gaowen and Bai,  Jieyun and Ou,  Zhanhong and Lu,  Yaosheng and Wang,  Huijin},
  year = {2024},
  month = may 
}

@article{amd-sd,
  title = {AMD-SD: An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation},
  volume = {11},
  ISSN = {2052-4463},
  url = {http://doi.org/10.1038/s41597-024-03844-6},
  DOI = {10.1038/s41597-024-03844-6},
  number = {1},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Hu,  Yunwei and Gao,  Yundi and Gao,  Weihao and Luo,  Wenbin and Yang,  Zhongyi and Xiong,  Fen and Chen,  Zidan and Lin,  Yucai and Xia,  Xinjing and Yin,  Xiaolong and Deng,  Yan and Ma,  Lan and Li,  Guodong},
  year = {2024},
  month = sep 
}

@article{mice-tumseg,
  title = {3D whole body preclinical micro-CT database of subcutaneous tumors in mice with annotations from 3 annotators},
  volume = {11},
  ISSN = {2052-4463},
  url = {http://doi.org/10.1038/s41597-024-03814-y},
  DOI = {10.1038/s41597-024-03814-y},
  number = {1},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Jensen,  Malte and Clemmensen,  Andreas and Hansen,  Jacob Gorm and van Krimpen Mortensen,  Julie and Christensen,  Emil N. and Kjaer,  Andreas and Ripa,  Rasmus Sejersten},
  year = {2024},
  month = sep 
}

@article{papila,
  title = {PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment},
  volume = {9},
  ISSN = {2052-4463},
  url = {http://doi.org/10.1038/s41597-022-01388-1},
  DOI = {10.1038/s41597-022-01388-1},
  number = {1},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Kovalyk,  Oleksandr and Morales-Sánchez,  Juan and Verdú-Monedero,  Rafael and Sellés-Navarro,  Inmaculada and Palazón-Cabanes,  Ana and Sancho-Gómez,  José-Luis},
  year = {2022},
  month = jun 
}

@article{jsrt,
  title = {Development of a Digital Image Database for Chest Radiographs With and Without a Lung Nodule: Receiver Operating Characteristic Analysis of Radiologists’ Detection of Pulmonary Nodules},
  volume = {174},
  ISSN = {1546-3141},
  url = {http://doi.org/10.2214/ajr.174.1.1740071},
  DOI = {10.2214/ajr.174.1.1740071},
  number = {1},
  journal = {American Journal of Roentgenology},
  publisher = {American Roentgen Ray Society},
  author = {Shiraishi,  Junji and Katsuragawa,  Shigehiko and Ikezoe,  Junpei and Matsumoto,  Tsuneo and Kobayashi,  Takeshi and Komatsu,  Ken-ichi and Matsui,  Mitate and Fujita,  Hiroshi and Kodera,  Yoshie and Doi,  Kunio},
  year = {2000},
  month = jan,
  pages = {71–74}
}

@article{motum,
  title = {A Multi-Center,  Multi-Parametric MRI Dataset of Primary and Secondary Brain Tumors},
  volume = {11},
  ISSN = {2052-4463},
  url = {http://doi.org/10.1038/s41597-024-03634-0},
  DOI = {10.1038/s41597-024-03634-0},
  number = {1},
  journal = {Scientific Data},
  publisher = {Springer Science and Business Media LLC},
  author = {Gong,  Zhenyu and Xu,  Tao and Peng,  Nan and Cheng,  Xing and Niu,  Chen and Wiestler,  Benedikt and Hong,  Fan and Li,  Hongwei Bran},
  year = {2024},
  month = jul 
}

@article{chen2024ma,
  title={Ma-sam: Modality-agnostic sam adaptation for 3d medical image segmentation},
  author={Chen, Cheng and Miao, Juzheng and Wu, Dufan and Zhong, Aoxiao and Yan, Zhiling and Kim, Sekeun and Hu, Jiang and Liu, Zhengliang and Sun, Lichao and Li, Xiang and others},
  journal={Medical Image Analysis},
  volume={98},
  pages={103310},
  year={2024},
  publisher={Elsevier},
  url={https://doi.org/10.1016/j.media.2024.103310}
}

@article{ravi2024sam,
  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 others},
  journal={ICLR},
  year={2025},
  url={https://openreview.net/forum?id=Ha6RTeWMd0}
}

@misc{bioicons,
  author = {Florian Jug and Bioicons Contributors},
  title = {Bioicons - Free Biology Icons},
  year = {2023},
  url = {https://bioicons.com/},
}

@misc{dbcls,
  author = {Database Center for Life Science (DBCLS)},
  title = {TogoTV - Life Science Video Portal},
  year = {2023},
  url = {https://togotv.dbcls.jp/en/pics.html},
}

@misc{bert,
  title={BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding}, 
  author={Jacob Devlin and Ming-Wei Chang and Kenton Lee and Kristina Toutanova},
  year={2019},
  eprint={1810.04805},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://doi.org/10.48550/arXiv.1810.04805}, 
}

@misc{llama2,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models}, 
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://doi.org/10.48550/arXiv.2307.09288}, 
}

@inproceedings{gpt3,
 author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared D and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and Herbert-Voss, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel and Wu, Jeffrey and Winter, Clemens and Hesse, Chris and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
 pages = {1877--1901},
 publisher = {Curran Associates, Inc.},
 title = {Language Models are Few-Shot Learners},
 url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf},
 volume = {33},
 year = {2020}
}

@article{wu2025trans,
  title={Trans-SAM: Transfer Segment Anything Model to medical image segmentation with Parameter-Efficient Fine-Tuning},
  author={Wu, Yanlin and Wang, Zhihong and Yang, Xiongfeng and Kang, Hong and He, Along and Li, Tao},
  journal={Knowledge-Based Systems},
  volume={310},
  pages={112909},
  year={2025},
  publisher={Elsevier},
  url = {https://doi.org/10.1016/j.knosys.2024.112909},
}
