4 papers
Iterative Diffusion-Refined Neural Attenuation Fields for Multi-Source Stationary CT Reconstruction: NAF Meets Diffusion Model
Jiancheng Fang, Shaoyu Wang, Junlin Wang +3
Multi-source stationary computed tomography (CT) has recently attracted attention for its ability to achieve rapid image reconstruction, making it suitable for time-sensitive clini…
Continuity-driven Synergistic Diffusion with Neural Priors for Ultra-Sparse-View CBCT Reconstruction
Junlin Wang, Jiancheng Fang, Peng Peng +2
The clinical application of cone-beam computed tomography (CBCT) is constrained by the inherent trade-off between radiation exposure and image quality. Ultra-sparse angular samplin…
FSP-Diff: Full-Spectrum Prior-Enhanced DualDomain Latent Diffusion for Ultra-Low-Dose Spectral CT Reconstruction
Peng Peng, Xinrui Zhang, Junlin Wang +3
Spectral computed tomography (CT) with photon-counting detectors holds immense potential for material discrimination and tissue characterization. However, under ultra-low-dose cond…
Machine learning assisted speckle and OAM spectrum analysis for enhanced turbulence characterisation
Wenjie Jiang, Mingjian Cheng, Lixin Guo +4
Atmospheric turbulence degrades the performance of free-space optical (FSO) communication and remote sensing systems by introducing phase and intensity distortions. While a majorit…