1 citations · 2 across the 12 of their papers we have counts for
6 papers · 1 filter
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…
An incremental algorithm for non-convex AI-enhanced medical image processing
Elena Morotti
Solving non-convex regularized inverse problems is challenging due to their complex optimization landscapes and multiple local minima. However, these models remain widely studied a…
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,…
Deep image prior inpainting of ancient frescoes in the Mediterranean Alpine arc
Fabio Merizzi, Perrine Saillard, Oceane Acquier +4
The unprecedented success of image reconstruction approaches based on deep neural networks has revolutionised both the processing and the analysis paradigms in several applied disc…
Ambiguity in solving imaging inverse problems with deep learning based operators
Davide Evangelista, Elena Morotti, Elena Loli Piccolomini +1
In recent years, large convolutional neural networks have been widely used as tools for image deblurring, because of their ability in restoring images very precisely. It is well kn…