60 citations · 147 across the 15 of their papers we have counts for
15 papers
STIX imaging I -- Concept
Paolo Massa, Gordon. J. Hurford, Anna Volpara +17
Aims. To provide a schematic mathematical description of the imaging concept of the Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter. The derived model is th…
Forward-fitting STIX visibilities
Anna Volpara, Paolo Massa, Emma Perracchione +6
Aima. To determine to what extent the problem of forward fitting visibilities measured by the Spectrometer/Telescope Imaging X-rays (STIX) on-board Solar Orbiter is more challengin…
First hard X-ray imaging results by Solar Orbiter STIX
Paolo Massa, Andrea F. Battaglia, Anna Volpara +15
Context. The Spectrometer/Telescope for Imaging X-rays (STIX) is one of 6 remote sensing instruments on-board Solar Orbiter. It provides hard X-ray imaging spectroscopy of solar fl…
Regularization from examples via neural networks for parametric inverse problems: topology matters
Paolo Massa, Sara Garbarino, Federico Benvenuto
In this work we deal with parametric inverse problems, which consist in recovering a finite number of parameters describing the structure of an unknown object, from indirect measur…
Imaging from STIX visibility amplitudes
Paolo Massa, Emma Perracchione, Sara Garbarino +5
Aims: To provide the first demonstration of STIX Fourier-transform X-ray imaging using semi-calibrated (amplitude-only) visibility data acquired during the Solar Orbiter's cruise p…
Modeling and inference of spatio-temporal protein dynamics across brain networks
Sara Garbarino, Marco Lorenzi
Models of misfolded proteins (MP) aim at discovering the bio-mechanical propagation properties of neurological diseases (ND) by identifying plausible associated dynamical systems.…
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Razvan V. Marinescu, Arman Eshaghi, Marco Lorenzi +5
Here we present DIVE: Data-driven Inference of Vertexwise Evolution. DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-te…
Iterative algorithms for a non-linear inverse problem in atmospheric lidar
Giulia Denevi, Sara Garbarino, Alberto Sorrentino
We consider the inverse problem of retrieving aerosol extinction coefficients from Raman lidar measurements. In this problem the unknown and the data are related through the expone…
Parametric Imaging of FDG-PET Data Using Physiology and Iterative Regularization: Application to the Hepatic and Renal Systems
Mara Scussolini, Sara Garbarino, Gianmario Sambuceti +2
The present paper proposes a novel computational method for parametric imaging of nuclear medicine data. The mathematical procedure is general enough to work for compartmental mode…
A physiology--based parametric imaging method for FDG--PET data
Mara Scussolini, Sara Garbarino, Gianmario Sambuceti +2
Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present…
Expectation Maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman lidar data
Sara Garbarino, Alberto Sorrentino, Anna Maria Massone +5
We consider the problem of retrieving the aerosol extinction coefficient from Raman lidar measurements. This is an ill--posed inverse problem that needs regularization, and we prop…
Compartmental analysis of dynamic nuclear medicine data: regularization procedure and application to physiology
Delbary Fabrice, Garbarino Sara
Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolis…
Compartmental analysis of dynamic nuclear medicine data: models and identifiability
Fabrice Delbary, Sara Garbarino, Valentina Vivaldi
Compartmental models based on tracer mass balance are extensively used in clinical and pre-clinical nuclear medicine in order to obtain quantitative information on tracer metabolis…
Compartmental analysis of nuclear imaging data for the quantification of FDG liver metabolism
Valentina Vivaldi, Sara Garbarino, Giacomo Caviglia +2
This paper utilizes compartmental analysis and a statistical optimization technique in order to reduce a compartmental model describing the metabolism of labelled glucose in liver.…
Compartmental analysis of renal physiology using nuclear medicine data and statistical optimization
Sara Garbarino, Giacomo Caviglia, Massimo Brignone +3
This paper describes a general approach to the compartmental modeling of nuclear data based on spectral analysis and statistical optimization. We utilize the renal physiology as te…