3 citations · 8 across the 7 of their papers we have counts for
7 papers
Graph Image Prior for Unsupervised Dynamic Cardiac Cine MRI Reconstruction
Zhongsen Li, Wenxuan Chen, Shuai Wang +3
The inductive bias of the convolutional neural network (CNN) can be a strong prior for image restoration, which is known as the Deep Image Prior (DIP). Recently, DIP is utilized in…
Towards Generalizable Medical Image Segmentation with Pixel-wise Uncertainty Estimation
Shuai Wang, Zipei Yan, Daoan Zhang +4
Deep neural networks (DNNs) achieve promising performance in visual recognition under the independent and identically distributed (IID) hypothesis. In contrast, the IID hypothesis…
Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation
Shuai Wang, Daoan Zhang, Zipei Yan +2
Source-free domain adaptation aims to adapt deep neural networks using only pre-trained source models and target data. However, accessing the source model still has a potential con…
Prototype Knowledge Distillation for Medical Segmentation with Missing Modality
Shuai Wang, Zipei Yan, Daoan Zhang +3
Multi-modality medical imaging is crucial in clinical treatment as it can provide complementary information for medical image segmentation. However, collecting multi-modal data in…
Bootstrap The Original Latent: Learning a Private Model from a Black-box Model
Shuai Wang, Daoan Zhang, Jianguo Zhang +2
In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users t…
Feature Alignment and Uniformity for Test Time Adaptation
Shuai Wang, Daoan Zhang, Zipei Yan +2
Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples. In this setting, the model can only access online unlabeled te…
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI
Zhongsen Li, Aiqi Sun, Chuyu Liu +4
Objective. Imaging dynamic object with high temporal resolution is challenging in magnetic resonance imaging (MRI). Partial separable (PS) model was proposed to improve the imaging…