Wenqi Li

发表

The future of digital health with federated learning.

Micah J. Sheller, Ronald M. Summers, Shadi Albarqouni, 2020, NPJ digital medicine.

Rapid Artificial Intelligence Solutions in a Pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge

Klaus H. Maier-Hein, Mona G. Flores, V. Kovalev, 2021, Research square.

Federated Learning for Breast Density Classification: A Real-World Implementation pdf

Daguang Xu, Jesse Tetreault, Ahmed Harouni, 2020, DART/DCL@MICCAI.

Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation

Vishal M. Patel, S. Harmon, H. Roth, 2022, ECCV.

Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge

Klaus H. Maier-Hein, Mona G. Flores, V. Kovalev, 2022, Medical Image Analysis.

Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation

Ziyue Xu, H. Roth, A. Myronenko, 2022, DeCaF/FAIR@MICCAI.

Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge

Klaus H. Maier-Hein, Mona G. Flores, V. Kovalev, 2022, Medical Image Analysis.

NVIDIA FLARE: Federated Learning from Simulation to Real-World

Sean Bin Yang, Mona G. Flores, Ziyue Xu, 2022, ArXiv.

MONAI: An open-source framework for deep learning in healthcare

Mohammad Zalbagi Darestani, Paul F. Jaeger, Brad W. Genereaux, 2022, ArXiv.

Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge

Mona G. Flores, V. Kovalev, V. Liauchuk, 2022, Medical image analysis.

NVIDIA FLARE: Federated Learning from Simulation to Real-World

Sean Bin Yang, Mona G. Flores, Ziyue Xu, 2022, ArXiv.

GradViT: Gradient Inversion of Vision Transformers

J. Kautz, H. Roth, Pavlo Molchanov, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

B. Landman, H. Roth, Ali Hatamizadeh, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

NVIDIA FLARE: Federated Learning from Simulation to Real-World

Sean Bin Yang, Mona G. Flores, Ziyue Xu, 2022, IEEE Data Eng. Bull..

Federated Learning for Breast Density Classification: A Real-World Implementation

Colin B. Compas, Richard D. White, Mona G. Flores, 2020, DART/DCL@MICCAI.

Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures pdf

Daguang Xu, Andriy Myronenko, Wentao Zhu, 2021, MICCAI.

MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images

S. Ourselin, Fernando Pérez-García, M. Cardoso, 2022, Medical Image Anal..

Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation

H. Roth, Ali Hatamizadeh, Daguang Xu, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image Segmentation

H. Roth, Ali Hatamizadeh, Daguang Xu, 2022, ArXiv.

Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation pdf

Daguang Xu, Baris Turkbey, Holger Roth, 2021, ArXiv.

Fair Federated Medical Image Segmentation via Client Contribution Estimation

Ziyue Xu, H. Roth, Daguang Xu, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Mona G. Flores, J. Kautz, H. Roth, 2022, IEEE Transactions on Medical Imaging.

Towards Understanding the Risks of Gradient Inversion in Federated Learning

Mona G. Flores, J. Kautz, H. Roth, 2021 .

Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples

Ziyue Xu, H. Roth, Daguang Xu, 2023, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge

Mona G. Flores, V. Kovalev, V. Liauchuk, 2022, Medical Image Analysis.

UNetFormer: A Unified Vision Transformer Model and Pre-Training Framework for 3D Medical Image Segmentation

H. Roth, Ali Hatamizadeh, Daguang Xu, 2022, arXiv.org.

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training

Vishal M. Patel, Jeya Maria Jose Valanarasu, Ziyue Xu, 2023, ArXiv.