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Consecutive Posterior Fusion for Diffusive Recovery of Unobservable Image Structures
Elena Morotti, Davide Evangelista, Elena Loli Piccolomini
Solving severely ill-posed imaging inverse problems requires recovering image structures that are unobservable or weakly constrained by the measurements. Diffusion models provide e…
Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration
Davide Evangelista, Elena Morotti, Francesco Pivi +1
Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Yet, its standard formulations r…
A Diffusion-Based Generative Prior Approach to Sparse-view Computed Tomography
Davide Evangelista, Pasquale Cascarano, Elena Loli Piccolomini
The reconstruction of X-rays CT images from sparse or limited-angle geometries is a highly challenging task. The lack of data typically results in artifacts in the reconstructed im…
LIP-CAR: contrast agent reduction by a deep learned inverse problem
Davide Bianchi, Sonia Colombo Serra, Davide Evangelista +3
The adoption of contrast agents in medical imaging protocols is crucial for accurate and timely diagnosis. While highly effective and characterized by an excellent safety profile,…