Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. - Micah J. Sheller; G. Anthony Reina; Brandon Edwards; Jason Martin; Spyridon Bakas (BrainLes@MICCAI (1), 2018)

The future of digital health with federated learning. - Nicola Rieke; Jonny Hancox; Wenqi Li 001; Fausto Milletarì; Holger R. Roth; Shadi Albarqouni; Spyridon Bakas; Mathieu N. Galtier; Bennett A. Landman; Klaus H. Maier-Hein; Sébastien Ourselin; Micah J. Sheller; et al. (npj Digit. Medicine, 2020)

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging. - Sarthak Pati; Siddhesh P. Thakur; Megh Bhalerao; Ujjwal Baid; Caleb M. Grenko; Brandon Edwards; Micah J. Sheller; Jose Agraz; Bhakti Baheti; Vishnu Bashyam; Parth Sharma; Babak Haghighi; et al. (CoRR, 2021)

The Federated Tumor Segmentation (FeTS) Challenge. - Sarthak Pati; Ujjwal Baid; Maximilian Zenk; Brandon Edwards; Micah J. Sheller; G. Anthony Reina; Patrick Foley; Alexey Gruzdev; Jason Martin; Shadi Albarqouni; Yong Chen 016; Russell Taki Shinohara; et al. (CoRR, 2021)

OpenFL: An open-source framework for Federated Learning. - G. Anthony Reina; Alexey Gruzdev; Patrick Foley; Olga Perepelkina; Mansi Sharma; Igor Davidyuk; Ilya Trushkin; Maksim Radionov; Aleksandr Mokrov; Dmitry Agapov; Jason Martin; Brandon Edwards; et al. (CoRR, 2021)

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Srini Bala; Daniel J. Beutel; Victor Bittorf; Akshay Chaudhari; Alexander Chowdhury; Cody Coleman; Bala Desinghu; et al. (CoRR, 2021)

Federated Learning Enables Big Data for Rare Cancer Boundary Detection. - Sarthak Pati; Ujjwal Baid; Brandon Edwards; Micah J. Sheller; Hans Shih-Han Wang; G. Anthony Reina; Patrick Foley; Alexey Gruzdev; Deepthi Karkada; Christos Davatzikos; Chiharu Sako; Satyam Ghodasara; et al. (CoRR, 2022)

Federated benchmarking of medical artificial intelligence with MedPerf. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Anna Wuest; Sarthak Pati; Hasan Kassem; Maximilian Zenk; Ujjwal Baid; Prakash Narayana Moorthy; Alexander Chowdhury; et al. (Nat. Mac. Intell., 2023)

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation. - Dominic LaBella; Katherine Schumacher; Michael Mix; Kevin Leu; Shan McBurney-Lin; Pierre Nedelec; Javier E. Villanueva-Meyer; Jonathan Shapey; Tom Vercauteren; Kazumi Chia; Omar Al-Salihi; Justin Leu; et al. (CoRR, 2024)

BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023. - Anahita Fathi Kazerooni; Nastaran Khalili; Xinyang Liu; Debanjan Haldar; Zhifan Jiang; Anna Zapaishchykova; Julija Pavaine; Lubdha M. Shah; Blaise V. Jones; Nakul Sheth; Sanjay P. Prabhu; Aaron S. McAllister; et al. (CoRR, 2024)

Privacy preservation for federated learning in health care. - Sarthak Pati; Sourav Kumar; Amokh Varma; Brandon Edwards; Charles Lu 001; Liangqiong Qu; Justin J. Wang; Anantharaman Lakshminarayanan; Shih-han Wang; Micah J. Sheller; Ken Chang; Praveer Singh; et al. (Patterns, 2024)