Diffusion Priors Enhance Sparse CT Reconstruction
Introduces diffusion-based generative priors in DGP framework for reconstructing CT images from sparse-view sinograms. Combines iterative optimization with neural generative power while preserving explainability. Shows promising results under highly sparse geometries.






