Diffusion priors for sparse-view CT work on synthetic data but face domain shift and forward model mismatch on experimental phantom data, with annealed likelihood weights offering partial mitigation.
Decomposed diffusion sampler for accelerating large-scale inverse problems,
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Towards reconstructing experimental sparse-view X-ray CT data with diffusion models
Diffusion priors for sparse-view CT work on synthetic data but face domain shift and forward model mismatch on experimental phantom data, with annealed likelihood weights offering partial mitigation.