3 papers
cs.CV2026
SCOUT: Fast Spectral CT Imaging in Ultra LOw-data Regimes via PseUdo-label GeneraTion
Guoquan Wei, Liu Shi, Shaoyu Wang +3
Noise and artifacts during computed tomography (CT) scans are a fundamental challenge affecting disease diagnosis. However, current methods either involve excessively long reconstr…
cs.CV2026
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…