3 citations · 4 across the 8 of their papers we have counts for
8 papers
Physics-Driven 3D Gaussian Rendering for Zero-Shot MRI Super-Resolution
Shuting Liu, Lei Zhang, Wei Huang +2
High-resolution Magnetic Resonance Imaging (MRI) is vital for clinical diagnosis but limited by long acquisition times and motion artifacts. Super-resolution (SR) reconstructs low-…
BinaryAttention: One-Bit QK-Attention for Vision and Diffusion Transformers
Chaodong Xiao, Zhengqiang Zhang, Lei Zhang
Transformers have achieved widespread and remarkable success, while the computational complexity of their attention modules remains a major bottleneck for vision tasks. Existing me…
Boundary-Aware Test-Time Adaptation for Zero-Shot Medical Image Segmentation
Chenlin Xu, Lei Zhang, Lituan Wang +5
Due to the scarcity of annotated data and the substantial computational costs of model, conventional tuning methods in medical image segmentation face critical challenges. Current…
EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation
Wang Lituan, Zhang Lei, Wang Yan +3
Weakly-supervised medical image segmentation is gaining traction as it requires only rough annotations rather than accurate pixel-to-pixel labels, thereby reducing the workload for…
Optical Flow Representation Alignment Mamba Diffusion Model for Medical Video Generation
Zhenbin Wang, Lei Zhang, Lituan Wang +2
Medical video generation models are expected to have a profound impact on the healthcare industry, including but not limited to medical education and training, surgical planning, a…
Soft Masked Mamba Diffusion Model for CT to MRI Conversion
Zhenbin Wang, Lei Zhang, Lituan Wang +1
Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the predominant modalities utilized in the field of medical imaging. Although MRI capture the complexity of anatom…
PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix Augmentation
Yu Lei, Haolun Luo, Lituan Wang +2
In weakly supervised medical image segmentation, the absence of structural priors and the discreteness of class feature distribution present a challenge, i.e., how to accurately pr…
LanDA: Language-Guided Multi-Source Domain Adaptation
Zhenbin Wang, Lei Zhang, Lituan Wang +1
Multi-Source Domain Adaptation (MSDA) aims to mitigate changes in data distribution when transferring knowledge from multiple labeled source domains to an unlabeled target domain.…