65 citations · 229 across the 24 of their papers we have counts for
9 papers · 1 filter
Asynchronous Federated Continual Segmentation with Evolving Clients and Label Spaces
Can Peng, Qianhui Men, Pramit Saha +5
Federated learning seeks to foster collaboration among distributed clients while preserving the privacy of their local data. Traditional federated learning methods typically assume…
The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion)
Shuo Wang, Chen Qin, Chengyan Wang +12
The quality of cardiac magnetic resonance (CMR) imaging is susceptible to respiratory motion artifacts. The model robustness of automated segmentation techniques in face of real-wo…
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation
Chen Chen, Zeju Li, Cheng Ouyang +3
Convolutional neural networks (CNNs) have achieved remarkable segmentation accuracy on benchmark datasets where training and test sets are from the same domain, yet their performan…
Enhancing MR Image Segmentation with Realistic Adversarial Data Augmentation
Chen Chen, Chen Qin, Cheng Ouyang +7
The success of neural networks on medical image segmentation tasks typically relies on large labeled datasets for model training. However, acquiring and manually labeling a large m…
Realistic Adversarial Data Augmentation for MR Image Segmentation
Chen Chen, Chen Qin, Huaqi Qiu +6
Neural network-based approaches can achieve high accuracy in various medical image segmentation tasks. However, they generally require large labelled datasets for supervised learni…
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge
Xiahai Zhuang, Jiahang Xu, Xinzhe Luo +20
Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suff…
Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction
Jo Schlemper, Jinming Duan, Cheng Ouyang +4
We present simple reconstruction networks for multi-coil data by extending deep cascade of CNN's and exploiting the data consistency layer. In particular, we propose two variants,…
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
Chen Chen, Cheng Ouyang, Giacomo Tarroni +4
In this work, we present a fully automatic method to segment cardiac structures from late-gadolinium enhanced (LGE) images without using labelled LGE data for training, but instead…
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
Jinming Duan, Jo Schlemper, Chen Qin +7
In this work, we propose a deep learning approach for parallel magnetic resonance imaging (MRI) reconstruction, termed a variable splitting network (VS-Net), for an efficient, high…