53 citations · 65 across the 7 of their papers we have counts for
9 papers
Spreading of pathological proteins through brain networks: a case study for Alzheimers disease
G. Landi, A. Scaravelli, M. C. Tesi +1
Mathematical modeling offers a valuable approach to understanding Alzheimers disease (AD) given its complexity, unknown causes, and lack of effective treatments. Models, once valid…
Uniform multi-penalty regularization for linear ill-posed inverse problems
Villiam Bortolotti, Germana Landi, Fabiana Zama
This study examines, in the framework of variational regularization methods, a multi-penalty regularization approach which builds upon the Uniform PENalty (UPEN) method, previously…
An automatic L1-based regularization method for the analysis of FFC dispersion profiles with quadrupolar peaks
Germana Landi, Giovanni V. Spinelli, Fabiana Zama +4
Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive technique to investigate molecular dynamics and structure of systems having a wide range of applicati…
MUPen2DTool: a Matlab Tool for 2D Nuclear Magnetic Resonance relaxation data inversion
Villiam Bortolotti, Leonardo Brizi, Germana Landi +2
Accurate and efficient analysis of materials properties from Nuclear Magnetic Resonance (NMR) relaxation data requires robust and efficient inversion procedures. Despite the great…
Directional TGV-based image restoration under Poisson noise
Daniela di Serafino, Germana Landi, Marco Viola
We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for exa…
TGV-based restoration of Poissonian images with automatic estimation of the regularization parameter
Daniela di Serafino, Germana Landi, Marco Viola
The problem of restoring images corrupted by Poisson noise is common in many application fields and, because of its intrinsic ill posedness, it requires regularization techniques f…
2DNMR data inversion using locally adapted multi-penalty regularization
Villiam Bortolotti, Germana Landi, Fabiana Zama
A crucial issue in two-dimensional Nuclear Magnetic Resonance (NMR) is the speed and accuracy of the data inversion. This paper proposes a multi-penalty method with locally adapted…
ACQUIRE: an inexact iteratively reweighted norm approach for TV-based Poisson image restoration
Daniela di Serafino, Germana Landi, Marco Viola
We propose a method, called ACQUIRE, for the solution of constrained optimization problems modeling the restoration of images corrupted by Poisson noise. The objective function is…
Uniform Penalty inversion of two-dimensional NMR Relaxation data
V. Bortolotti, R. J. S. Brown, P. Fantazzini +2
The inversion of two-dimensional NMR data is an ill-posed problem related to the numerical computation of the inverse Laplace transform. In this paper we present the 2DUPEN algorit…