1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
Space-Variant Total Variation boosted by learning techniques in few-view tomographic imaging
Elena Morotti, Davide Evangelista, Andrea Sebastiani +1
This paper focuses on the development of a space-variant regularization model for solving an under-determined linear inverse problem. The case study is a medical image reconstructi…
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…