5 papers
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 Line--Search--Based Stochastic Gradient Method for 3D Computed Tomography
Tatiana A. Bubba, Elena Morotti, Federica Porta +2
We introduce FB-LISA, a forward-backward (FB) generalization of a recently proposed line-search-based stochastic gradient algorithm to address the imaging problem of volumetric rec…
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…
Adaptive Weighted Total Variation boosted by learning techniques in few-view tomographic imaging
Elena Morotti, Davide Evangelista, Andrea Sebastiani +1
This study presents the development of a spatially adaptive weighting strategy for Total Variation regularization, aimed at addressing under-determined linear inverse problems. The…
Deep Guess acceleration for explainable image reconstruction in sparse-view CT
Elena Loli Piccolomini, Davide Evangelista, Elena Morotti
Sparse-view Computed Tomography (CT) is an emerging protocol designed to reduce X-ray dose radiation in medical imaging. Traditional Filtered Back Projection algorithm reconstructi…