17 citations · 24 across the 12 of their papers we have counts for
4 papers · 1 filter
FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising
Zhihao Chen, Qi Gao, Zilong Li +4
Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despite significant advancements drive…
Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction
Qi Gao, Zhihao Chen, Dong Zeng +3
The generalization of deep learning-based low-dose computed tomography (CT) reconstruction models to doses unseen in the training data is important and remains challenging. Previou…
PROTOCOL: Partial Optimal Transport-enhanced Contrastive Learning for Imbalanced Multi-view Clustering
Xuqian Xue, Yiming Lei, Qi Cai +2
While contrastive multi-view clustering has achieved remarkable success, it implicitly assumes balanced class distribution. However, real-world multi-view data primarily exhibits c…
Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction
Chenglong Ma, Zilong Li, Yuanlin Li +5
Metal artifacts in computed tomography (CT) images can significantly degrade image quality and impede accurate diagnosis. Supervised metal artifact reduction (MAR) methods, trained…