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@misc{zhu2019deep,
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      year={2019},
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      archivePrefix={arXiv},
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@misc{zhao2020idlg,
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      author={Bo Zhao and Konda Reddy Mopuri and Hakan Bilen},
      year={2020},
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      archivePrefix={arXiv},
      primaryClass={cs.LG}
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}
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@article{fan2020rethinking,
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}
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  title={See through gradients: Image batch recovery via gradinversion},
  author={Yin, Hongxu and Mallya, Arun and Vahdat, Arash and Alvarez, Jose M and Kautz, Jan and Molchanov, Pavlo},
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@misc{dimitrov2022data,
      title={Data Leakage in Federated Averaging}, 
      author={Dimitar I. Dimitrov and Mislav Balunović and Nikola Konstantinov and Martin Vechev},
      year={2022},
      eprint={2206.12395},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@misc{wen2022fishing,
      title={Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification}, 
      author={Yuxin Wen and Jonas Geiping and Liam Fowl and Micah Goldblum and Tom Goldstein},
      year={2022},
      eprint={2202.00580},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@misc{pasquini2022eluding,
      title={Eluding Secure Aggregation in Federated Learning via Model Inconsistency}, 
      author={Dario Pasquini and Danilo Francati and Giuseppe Ateniese},
      year={2022},
      eprint={2111.07380},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@misc{fowl2022robbing,
      title={Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models}, 
      author={Liam Fowl and Jonas Geiping and Wojtek Czaja and Micah Goldblum and Tom Goldstein},
      year={2022},
      eprint={2110.13057},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@misc{boenisch2023curious,
      title={When the Curious Abandon Honesty: Federated Learning Is Not Private}, 
      author={Franziska Boenisch and Adam Dziedzic and Roei Schuster and Ali Shahin Shamsabadi and Ilia Shumailov and Nicolas Papernot},
      year={2023},
      eprint={2112.02918},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
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@inproceedings{wang2019beyond,
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@misc{brett2020nipy,
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doi = {10.21227/1jny-g144},
url = {https://dx.doi.org/10.21227/1jny-g144},
author = {Chaki, Jyotismita and Wozniak, Marcin},
publisher = {IEEE Dataport},
title = {Brain Tumor MRI Dataset},
year = {2023} }


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@article{matschinske2023featurecloud,
  title={The FeatureCloud platform for federated learning in biomedicine: unified approach},
  author={Matschinske, Julian and Sp{\"a}th, Julian and Bakhtiari, Mohammad and Probul, Niklas and Majdabadi, Mohammad Mahdi Kazemi and Nasirigerdeh, Reza and Torkzadehmahani, Reihaneh and Hartebrodt, Anne and Orban, Balazs-Attila and Fej{\'e}r, S{\'a}ndor-J{\'o}zsef and others},
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@article{liu2023recent,
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@online{NVFlare,
author = {NVFlare},
title = {{NVIDIA FLARE: Federated Learning from Simulation to Real-World}},
url = {https://developer.nvidia.com/flare},
urldate = {2024-02-02}
}


@online{MonaiFL,
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url = {https://docs.monai.io/en/latest/fl.html},
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@software{MITK_Team_MITK_2023,
author = {MITK Team},
license = {BSD-3-Clause},
month = nov,
title = {{MITK}},
url = {https://github.com/MITK/MITK},
version = {v2023.12},
year = {2023}
}

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