Fetching the paper…
Reading the bibliography…
Federated learning allows distributed medical institutions to collaboratively learn a shared prediction model with privacy protection.
The fast fourier transform
Henri J Nussbaumer · 1981
Earlier work this paper cites.
A demonstration of the visual importance and flexibility of spatial-frequency amplitude and phase
Leon N Piotrowski and Fergus W Campbell · 1982
Earlier work this paper cites.
The gridding method for image reconstruction by fourier transformation
Hermann Schomberg and Jan Timmer · 1995
Earlier work this paper cites.
Image phase or amplitude? rapid scene categorization is an amplitude-based process
Nathalie Guyader, Alan Chauvin, Carole Peyrin, Jeanny Hérault, and Christian Marendaz · 2004
Earlier work this paper cites.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
Earlier work this paper cites.
Rim-one: An open retinal image database for optic nerve evaluation
Francisco Fumero, Silvia Alayón, José L Sanchez, Jose Sigut, and M Gonzalez-Hernandez · 2011
Earlier work this paper cites.
Undoing the damage of dataset bias
Aditya Khosla, Tinghui Zhou, Tomasz Malisiewicz, Alexei A Efros, and Antonio Torralba · 2012
Earlier work this paper cites.
Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
Earlier work this paper cites.
Evaluation of prostate segmentation algorithms for mri: the promise12 challenge
Geert Litjens, Robert Toth, Wendy van de Ven, Caroline Hoeks, Sjoerd Kerkstra, Bram van Ginneken, Graham Vincent, Gwenael Guillard, Neil Birbeck, Jindang Zhang, et al · 2014
Earlier work this paper cites.
Nci-isbi 2013 challenge: automated segmentation of prostate structures
N Bloch, A Madabhushi, H Huisman, J Freymann, J Kirby, M Grauer, A Enquobahrie, C Jaffe, L Clarke, and K Farahani · 2015
Earlier work this paper cites.
Domain generalization for object recognition with multi-task autoencoders
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, and David Balduzzi · 2015
Earlier work this paper cites.
Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri: a review
Guillaume Lemaître, Robert Martí, Jordi Freixenet, Joan C Vilanova, Paul M Walker, and Fabrice Meriaudeau · 2015
Earlier work this paper cites.
A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis
Jayanthi Sivaswamy, S Krishnadas, Arunava Chakravarty, G Joshi, A Syed Tabish, et al · 2015
Earlier work this paper cites.
Federated learning: Strategies for improving communication efficiency
Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
Earlier work this paper cites.
Learning to cluster in order to transfer across domains and tasks
Yen-Chang Hsu, Zhaoyang Lv, and Zsolt Kira · 2017
Earlier work this paper cites.
Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
Earlier work this paper cites.
Learning to generalize: Meta-learning for domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
Earlier work this paper cites.
Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
Earlier work this paper cites.
Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A Adjeroh, and Gianfranco Doretto · 2017
Earlier work this paper cites.
Metareg: Towards domain generalization using meta-regularization
Yogesh Balaji, Swami Sankaranarayanan, and Rama Chellappa · 2018
Earlier work this paper cites.
Domain generalization with adversarial feature learning
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot · 2018
Earlier work this paper cites.
Deep domain generalization via conditional invariant adversarial networks
Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, and Dacheng Tao · 2018
Cited alongside, same era.
Generalizing across domains via cross-gradient training
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, and Sunita Sarawagi · 2018
Cited alongside, same era.
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, and Spyridon Bakas · 2018
Cited alongside, same era.
Generalizing to unseen domains via adversarial data augmentation
Riccardo Volpi, Hongseok Namkoong, Ozan Sener, John C Duchi, Vittorio Murino, and Silvio Savarese · 2018
Cited alongside, same era.
Domain generalization by solving jigsaw puzzles
Fabio M Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
Cited alongside, same era.
Augment your batch: Improving generalization through instance repetition
Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, and Daniel Soudry · 2020
Later among the works it cites.
Federated visual classification with real-world data distribution
Tzu-Ming Harry Hsu, Hang Qi, and Matthew Brown · 2020
Later among the works it cites.
Self-challenging improves cross-domain generalization
Zeyi Huang, Haohan Wang, Eric P Xing, and Dong Huang · 2020
Later among the works it cites.
Secure, privacy-preserving and federated machine learning in medical imaging
Georgios A Kaissis, Marcus R Makowski, Daniel Rückert, and Rickmer F Braren · 2020
Later among the works it cites.
Federated simulation for medical imaging
Daiqing Li, Amlan Kar, Nishant Ravikumar, Alejandro F Frangi, and Sanja Fidler · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Domain generalization via model-agnostic learning of semantic features
Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, and Ben Glocker · 2019
Cited alongside, same era.
Dlow: Domain flow for adaptation and generalization
Rui Gong, Wen Li, Yuhua Chen, and Luc Van Gool · 2019
Cited alongside, same era.
Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M Hospedales · 2019
Cited alongside, same era.
Privacy-preserving federated brain tumour segmentation
Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M Jorge Cardoso, et al · 2019
Cited alongside, same era.
Feature-critic networks for heterogeneous domain generalization
Yiying Li, Yongxin Yang, Wei Zhou, and Timothy M. Hospedales · 2019
Cited alongside, same era.
Federated adversarial domain adaptation
Xingchao Peng, Zijun Huang, Yizhe Zhu, and Kate Saenko · 2019
Cited alongside, same era.
Federated learning in distributed medical databases: Meta-analysis of large-scale subcortical brain data
Santiago Silva, Boris A Gutman, Eduardo Romero, Paul M Thompson, Andre Altmann, and Marco Lorenzi · 2019
Cited alongside, same era.
Xiaoxiao Li, Yufeng Gu, Nicha Dvornek, Lawrence Staib, Pamela Ventola, and James S Duncan · 2020
Later among the works it cites.
Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains
Quande Liu, Qi Dou, and Pheng-Ann Heng · 2020
Later among the works it cites.
Ms-net: Multi-site network for improving prostate segmentation with heterogeneous mri data
Quande Liu, Qi Dou, Lequan Yu, and Pheng Ann Heng · 2020
Later among the works it cites.
Domain generalization using a mixture of multiple latent domains
Toshihiko Matsuura and Tatsuya Harada · 2020
Later among the works it cites.
Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
José Ignacio Orlando, Huazhu Fu, João Barbosa Breda, Karel van Keer, Deepti R Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, JoonHo Lee, et al · 2020
Later among the works it cites.
Learning to learn single domain generalization
Fengchun Qiao, Long Zhao, and Xi Peng · 2020
Later among the works it cites.
The future of digital health with federated learning
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N Galtier, Bennett Landman, Klaus Maier-Hein, et al · 2020
Later among the works it cites.
Federated learning for breast density classification: A real-world implementation
Holger R Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C Bizzo, et al · 2020
Later among the works it cites.
Learning to optimize domain specific normalization for domain generalization
Seonguk Seo, Yumin Suh, Dongwan Kim, Jongwoo Han, and Bohyung Han · 2020
Later among the works it cites.
Axes of a revolution: challenges and promises of big data in healthcare
Smadar Shilo, Hagai Rossman, and Eran Segal · 2020
Later among the works it cites.
Learning from extrinsic and intrinsic supervisions for domain generalization
Shujun Wang, Lequan Yu, Caizi Li, Chi-Wing Fu, and Pheng-Ann Heng · 2020
Later among the works it cites.
Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets
Shujun Wang, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu, and Pheng-Ann Heng · 2020
Later among the works it cites.
Phase consistent ecological domain adaptation
Yanchao Yang, Dong Lao, Ganesh Sundaramoorthi, and Stefano Soatto · 2020
Later among the works it cites.
Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation
Ling Zhang, Xiaosong Wang, Dong Yang, Thomas Sanford, Stephanie Harmon, Baris Turkbey, Bradford J Wood, Holger Roth, Andriy Myronenko, Daguang Xu, and Ziyue Xu · 2020
Later among the works it cites.
Learning to generate novel domains for domain generalization
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang · 2020
Later among the works it cites.