@article{knoll2020fastmri,
  title={fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning},
  author={Knoll, Florian and Zbontar, Jure and Sriram, Anuroop and Muckley, Matthew J and Bruno, Mary and Defazio, Aaron and Parente, Marc and Geras, Krzysztof J and Katsnelson, Joe and Chandarana, Hersh and others},
  journal={Radiology: Artificial Intelligence},
  volume={2},
  number={1},
  pages={e190007},
  year={2020},
  publisher={Radiological Society of North America}
}
@article{zbontar2018fastmri,
  title={fastMRI: An open dataset and benchmarks for accelerated MRI},
  author={Zbontar, Jure and Knoll, Florian and Sriram, Anuroop and Murrell, Tullie and Huang, Zhengnan and Muckley, Matthew J and Defazio, Aaron and Stern, Ruben and Johnson, Patricia and Bruno, Mary and others},
  journal={arXiv preprint arXiv:1811.08839},
  year={2018}
}
@inproceedings{sriram2020end,
  title={End-to-end variational networks for accelerated MRI reconstruction},
  author={Sriram, Anuroop and Zbontar, Jure and Murrell, Tullie and Defazio, Aaron and Zitnick, C Lawrence and Yakubova, Nafissa and Knoll, Florian and Johnson, Patricia},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2020: 23rd International Conference, Lima, Peru, October 4--8, 2020, Proceedings, Part II 23},
  pages={64--73},
  year={2020},
  organization={Springer}
}
@inproceedings{bourtoule2021machine,
  title={Machine unlearning},
  author={Bourtoule, Lucas and Chandrasekaran, Varun and Choquette-Choo, Christopher A and Jia, Hengrui and Travers, Adelin and Zhang, Baiwu and Lie, David and Papernot, Nicolas},
  booktitle={2021 IEEE Symposium on Security and Privacy (SP)},
  pages={141--159},
  year={2021},
  organization={IEEE}
}

@article{regulation2018general,
  title={General data protection regulation (GDPR)},
  author={Regulation, General Data Protection},
  journal={Intersoft Consulting, Accessed in October},
  volume={24},
  number={1},
  year={2018}
}
@article{li2024machine,
  title={Machine Unlearning for Image-to-Image Generative Models},
  author={Li, Guihong and Hsu, Hsiang and Marculescu, Radu and others},
  journal={arXiv preprint arXiv:2402.00351},
  year={2024}
}
@article{nguyen2022survey,
  title={A survey of machine unlearning},
  author={Nguyen, Thanh Tam and Huynh, Thanh Trung and Nguyen, Phi Le and Liew, Alan Wee-Chung and Yin, Hongzhi and Nguyen, Quoc Viet Hung},
  journal={arXiv preprint arXiv:2209.02299},
  year={2022}
}
@article{bhadra2021hallucinations,
  title={On hallucinations in tomographic image reconstruction},
  author={Bhadra, Sayantan and Kelkar, Varun A and Brooks, Frank J and Anastasio, Mark A},
  journal={IEEE transactions on medical imaging},
  volume={40},
  number={11},
  pages={3249--3260},
  year={2021},
  publisher={IEEE}
}
@inproceedings{darestani2021measuring,
  title={Measuring robustness in deep learning based compressive sensing},
  author={Darestani, Mohammad Zalbagi and Chaudhari, Akshay S and Heckel, Reinhard},
  booktitle={International Conference on Machine Learning},
  pages={2433--2444},
  year={2021},
  organization={PMLR}
}
@article{xu2023machine,
  title={Machine unlearning: A survey},
  author={Xu, Heng and Zhu, Tianqing and Zhang, Lefeng and Zhou, Wanlei and Yu, Philip S},
  journal={ACM Computing Surveys},
  volume={56},
  number={1},
  pages={1--36},
  year={2023},
  publisher={ACM New York, NY, USA}
}
@article{akccakaya2019scan,
  title={Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging},
  author={Ak{\c{c}}akaya, Mehmet and Moeller, Steen and Weing{\"a}rtner, Sebastian and U{\u{g}}urbil, K{\^a}mil},
  journal={Magnetic resonance in medicine},
  volume={81},
  number={1},
  pages={439--453},
  year={2019},
  publisher={Wiley Online Library}
}
@inproceedings{wang2016accelerating,
  title={Accelerating magnetic resonance imaging via deep learning},
  author={Wang, Shanshan and Su, Zhenghang and Ying, Leslie and Peng, Xi and Zhu, Shun and Liang, Feng and Feng, Dagan and Liang, Dong},
  booktitle={2016 IEEE 13th international symposium on biomedical imaging (ISBI)},
  pages={514--517},
  year={2016},
  organization={IEEE}
}
@article{schlemper2017deep,
  title={A deep cascade of convolutional neural networks for dynamic MR image reconstruction},
  author={Schlemper, Jo and Caballero, Jose and Hajnal, Joseph V and Price, Anthony N and Rueckert, Daniel},
  journal={IEEE transactions on Medical Imaging},
  volume={37},
  number={2},
  pages={491--503},
  year={2017},
  publisher={IEEE}
}
@article{ginart2019making,
  title={Making ai forget you: Data deletion in machine learning},
  author={Ginart, Antonio and Guan, Melody and Valiant, Gregory and Zou, James Y},
  journal={Advances in neural information processing systems},
  volume={32},
  year={2019}
}
@article{antun2020instabilities,
  title={On instabilities of deep learning in image reconstruction and the potential costs of AI},
  author={Antun, Vegard and Renna, Francesco and Poon, Clarice and Adcock, Ben and Hansen, Anders C},
  journal={Proceedings of the National Academy of Sciences},
  volume={117},
  number={48},
  pages={30088--30095},
  year={2020},
  publisher={National Acad Sciences}
}
@inproceedings{neel2021descent,
  title={Descent-to-delete: Gradient-based methods for machine unlearning},
  author={Neel, Seth and Roth, Aaron and Sharifi-Malvajerdi, Saeed},
  booktitle={Algorithmic Learning Theory},
  pages={931--962},
  year={2021},
  organization={PMLR}
}
@article{tarun2023fast,
  title={Fast yet effective machine unlearning},
  author={Tarun, Ayush K and Chundawat, Vikram S and Mandal, Murari and Kankanhalli, Mohan},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2023},
  publisher={IEEE}
}
@inproceedings{chourasia2023forget,
  title={Forget unlearning: Towards true data-deletion in machine learning},
  author={Chourasia, Rishav and Shah, Neil},
  booktitle={International Conference on Machine Learning},
  pages={6028--6073},
  year={2023},
  organization={PMLR}
}
@article{jia2023model,
  title={Model sparsification can simplify machine unlearning},
  author={Jia, Jinghan and Liu, Jiancheng and Ram, Parikshit and Yao, Yuguang and Liu, Gaowen and Liu, Yang and Sharma, Pranay and Liu, Sijia},
  journal={arXiv preprint arXiv:2304.04934},
  year={2023}
}
@inproceedings{graves2021amnesiac,
  title={Amnesiac machine learning},
  author={Graves, Laura and Nagisetty, Vineel and Ganesh, Vijay},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={35},
  pages={11516--11524},
  year={2021}
}
@article{hartley2023neural,
  title={Neural networks memorise personal information from one sample},
  author={Hartley, John and Sanchez, Pedro P and Haider, Fasih and Tsaftaris, Sotirios A},
  journal={Scientific Reports},
  volume={13},
  number={1},
  pages={21366},
  year={2023},
  publisher={Nature Publishing Group UK London}
}
@article{dinsdale2021deep,
  title={Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal},
  author={Dinsdale, Nicola K and Jenkinson, Mark and Namburete, Ana IL},
  journal={NeuroImage},
  volume={228},
  pages={117689},
  year={2021},
  publisher={Elsevier}
}
@article{gandikota2023erasing,
  title={Erasing concepts from diffusion models},
  author={Gandikota, Rohit and Materzynska, Joanna and Fiotto-Kaufman, Jaden and Bau, David},
  journal={arXiv preprint arXiv:2303.07345},
  year={2023}
}
@article{halimi2022federated,
  title={Federated unlearning: How to efficiently erase a client in fl?},
  author={Halimi, Anisa and Kadhe, Swanand and Rawat, Ambrish and Baracaldo, Nathalie},
  journal={arXiv preprint arXiv:2207.05521},
  year={2022}
}
@article{warnecke2021machine,
  title={Machine unlearning of features and labels},
  author={Warnecke, Alexander and Pirch, Lukas and Wressnegger, Christian and Rieck, Konrad},
  journal={arXiv preprint arXiv:2108.11577},
  year={2021}
}
@inproceedings{ozturkler2023smrd,
  title={SMRD: SURE-Based Robust MRI Reconstruction with Diffusion Models},
  author={Ozturkler, Batu and Liu, Chao and Eckart, Benjamin and Mardani, Morteza and Song, Jiaming and Kautz, Jan},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={199--209},
  year={2023},
  organization={Springer}
}
@article{wang2004image,
  title={Image quality assessment: from error visibility to structural similarity},
  author={Wang, Zhou and Bovik, Alan C and Sheikh, Hamid R and Simoncelli, Eero P},
  journal={IEEE transactions on image processing},
  volume={13},
  number={4},
  pages={600--612},
  year={2004},
  publisher={IEEE}
}
@inproceedings{liu2020have,
  title={Have you forgotten? A method to assess if machine learning models have forgotten data},
  author={Liu, Xiao and Tsaftaris, Sotirios A},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2020: 23rd International Conference, Lima, Peru, October 4--8, 2020, Proceedings, Part I 23},
  pages={95--105},
  year={2020},
  organization={Springer}
}
@article{ashraf2018learning,
  title={Learning to unlearn: Building immunity to dataset bias in medical imaging studies},
  author={Ashraf, Ahmed and Khan, Shehroz and Bhagwat, Nikhil and Chakravarty, Mallar and Taati, Babak},
  journal={arXiv preprint arXiv:1812.01716},
  year={2018}
}
@inproceedings{su2022patient,
  title={Why patient data cannot be easily forgotten?},
  author={Su, Ruolin and Liu, Xiao and Tsaftaris, Sotirios A},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={632--641},
  year={2022},
  organization={Springer}
}
@inproceedings{teney2021unshuffling,
  title={Unshuffling data for improved generalization in visual question answering},
  author={Teney, Damien and Abbasnejad, Ehsan and van den Hengel, Anton},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={1417--1427},
  year={2021}
}