4 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…
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…
UniSino: Physics-Driven Foundational Model for Universal CT Sinogram Standardization
Xingyu Ai, Shaoyu Wang, Zhiyuan Jia +4
During raw-data acquisition in CT imaging, diverse factors can degrade the collected sinograms, with undersampling and noise leading to severe artifacts and noise in reconstructed…