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2020 – today
- 2022
[i7]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, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus H. Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey D. Rudie, Javier E. Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, et al.:
Federated Learning Enables Big Data for Rare Cancer Boundary Detection. CoRR abs/2204.10836 (2022)- 2021
- [i6]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, Aimilia Gastounioti, Mark Bergman, Bjoern H. Menze, Despina Kontos, Christos Davatzikos, Spyridon Bakas:
GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging. CoRR abs/2103.01006 (2021) - [i5]Sarthak Pati, Ujjwal Baid, Maximilian Zenk, Brandon Edwards, Micah J. Sheller, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Jason Martin, Shadi Albarqouni, Yong Chen, Russell Taki Shinohara, Annika Reinke, David Zimmerer, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab
, Marc-André Weber, Abhishek Mahajan, Lena Maier-Hein, Jens Kleesiek, Bjoern H. Menze, Klaus H. Maier-Hein, Spyridon Bakas:
The Federated Tumor Segmentation (FeTS) Challenge. CoRR abs/2105.05874 (2021) - [i4]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, Micah J. Sheller, Sarthak Pati, Prakash Narayana Moorthy, Hans Shih-Han Wang, Prashant Shah, Spyridon Bakas:
OpenFL: An open-source framework for Federated Learning. CoRR abs/2105.06413 (2021) - [i3]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, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson:
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR abs/2110.01406 (2021) - 2020
- [j1]Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletarì, Holger R. Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso:
The future of digital health with federated learning. npj Digit. Medicine 3 (2020) - [i2]Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso:
The Future of Digital Health with Federated Learning. CoRR abs/2003.08119 (2020)
2010 – 2019
- 2018
- [c1]Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas:
Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. BrainLes@MICCAI (1) 2018: 92-104 - [i1]Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas:
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. CoRR abs/1810.04304 (2018)
Coauthor Index
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