44 citations · 46 across the 8 of their papers we have counts for
5 papers · 1 filter
UniH: Unifying Hierarchical Homogeneity and Heterogeneity for All-in-One Medical Image Restoration
Zhiwen Yang, Jiayin Li, Chengyu Liu +3
All-in-One medical image restoration (MedIR) aims to address diverse tasks across modalities and degradation types using a single universal model. Existing methods typically priori…
TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration
Zhiwen Yang, Jiaju Zhang, Yang Yi +3
Medical image restoration (MedIR) aims to recover high-quality medical images from their low-quality counterparts. Recent advancements in MedIR have focused on All-in-One models ca…
All-in-One Medical Image Restoration with Latent Diffusion-Enhanced Vector-Quantized Codebook Prior
Haowei Chen, Zhiwen Yang, Haotian Hou +4
All-in-one medical image restoration (MedIR) aims to address multiple MedIR tasks using a unified model, concurrently recovering various high-quality (HQ) medical images (e.g., MRI…
FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation
Huihan Wang, Zhiwen Yang, Hui Zhang +3
Synthesizing high-quality dynamic medical videos remains a significant challenge due to the need for modeling both spatial consistency and temporal dynamics. Existing Transformer-b…
All-In-One Medical Image Restoration via Task-Adaptive Routing
Zhiwen Yang, Haowei Chen, Ziniu Qian +5
Although single-task medical image restoration (MedIR) has witnessed remarkable success, the limited generalizability of these methods poses a substantial obstacle to wider applica…