8 papers · 1 filter
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…
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…
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…