5 papers
Physics-Driven Independent Pair Generation for Iterative Self-Supervised Low-Dose CT Denoising
Xianlei Han, Shaoyu Wang, Jiancheng Fang +2
Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image statistics and do not explicitly…
Shared-Structure 4D Spectral Gaussian Representation for Sparse-View Spectral CT Reconstruction
Jiancheng Fang, Shaoyu Wang, Wenjun Xia +2
Sparse-view spectral computed tomography (CT) reconstructs energy-resolved attenuation volumes from limited projection views, requiring simultaneous handling of angular undersampli…
Residual Gaussian Splatting for Ultra Sparse-View CBCT Reconstruction
Jian Lin, Jiancheng Fang, Shaoyu Wang +4
While 3D Gaussian splatting (3DGS) offers explicit and efficient scene representations for cone-beam computed tomography reconstruction, conventional photometric optimization inher…
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…
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…