5 papers
UniSino: Physics-Driven Foundational Model for Universal CT Sinogram Standardization
Xingyu Ai, Shaoyu Wang, Zhiyuan Jia +4
During raw-data acquisition in CT imaging, diverse factors can degrade the collected sinograms, with undersampling and noise leading to severe artifacts and noise in reconstructed…
Ordered-subsets Multi-diffusion Model for Sparse-view CT Reconstruction
Pengfei Yu, Bin Huang, Minghui Zhang +3
Score-based diffusion models have shown significant promise in the field of sparse-view CT reconstruction. However, the projection dataset is large and riddled with redundancy. Con…
Virtual-mask Informed Prior for Sparse-view Dual-Energy CT Reconstruction
Zini Chen, Yao Xiao, Junyan Zhang +3
Sparse-view sampling in dual-energy computed tomography (DECT) significantly reduces radiation dose and increases imaging speed, yet is highly prone to artifacts. Although diffusio…
RED: Residual Estimation Diffusion for Low-Dose PET Sinogram Reconstruction
Xingyu Ai, Bin Huang, Fang Chen +4
Recent advances in diffusion models have demonstrated exceptional performance in generative tasks across vari-ous fields. In positron emission tomography (PET), the reduction in tr…
Zero-shot Dynamic MRI Reconstruction with Global-to-local Diffusion Model
Yu Guan, Kunlong Zhang, Qi Qi +5
Diffusion models have recently demonstrated considerable advancement in the generation and reconstruction of magnetic resonance imaging (MRI) data. These models exhibit great poten…