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cs.CV2025
Extendable Generalization Self-Supervised Diffusion for Low-Dose CT Reconstruction
Guoquan Wei, Liu Shi, Zekun Zhou +4
Current methods based on deep learning for self-supervised low-dose CT (LDCT) reconstruction, while reducing the dependence on paired data, face the problem of significantly decrea…
eess.IV2025
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…