Publications associées à Médecine nucléaire

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Julien René Pierre Fageot, Adrien Raphaël Depeursinge, Daniel Abler

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...

Nature Portfolio2024

Integrated electronics for time-of-flight positron emission tomography photodetectors

Andrada Alexandra Muntean

Positron emission tomography is a nuclear imaging technique well known for its use in oncology for cancer diagnosis and staging. A PET scanner is a complex machine which comprises photodetectors placed in a ring configuration that detect gamma photons gen ...

EPFL2023

X-ray qualification of hydrogenated amorphous silicon sensors on flexible substrate

Sylvain Dunand, Mikaël Martino, Nicolas Würsch, Luca Massimiliano Antognini, Matthew James Large

Hydrogenated amorphous silicon (a-Si:H) is a well known material for its radiation resistance and for the possibility of deposition on flexible substrates like Polyimide (PI), polyethylene terephthalate (PET) or polyethylene naphthalate (PEN). Due to the p ...

IEEE2023

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Bénédicte Marie Maréchal, Ricardo Alberto Corredor Jerez

Background: Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and ...

Springernature2023

3-D contact and pore network analysis of MICP cemented sands

Dimitrios Terzis, Nimisha Roy

The study describes a comprehensive methodology to evaluate X-Ray micro-computed tomography data from sand samples and to characterize their 3D microstructural properties. Fine and medium-grained sands are analyzed in their natural and bio-cemented states. ...

SPRINGER2023

Three-dimensional micro-CT images of UV-frozen flow fronts recorded at different flow regimes

Véronique Michaud, Jacobus Gerardus Rudolph Staal

Segmented micro-CT images of flow fronts produced by UV-flow freezing. Front morphologies correspond to capilary-dominated, equilibrated and viscous-dominated flow regimes. ...

Zenodo2023

Brain morphometry in older adults with and without dementia using extremely rapid structural scans

Tobias Kober, Tom Hilbert

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Locomotion of Sensor‐Integrated Soft Robotic Devices Inside Sub‐Millimeter Arteries with Impaired Flow Conditions

Diego Ghezzi, Mahmut Selman Sakar, Lorenzo Francesco John Noseda, Amit Yedidia Dolev, Lucio Feo Pancaldi-Giubbini, Adele Fanelli

One of the grand challenges in interventional cardiology and neuroradiology is to minimize the operation time and risk of damage during catheterization. These two factors drastically increase if the target location resides in small and tortuous vessels. Fl ...

Wiley2022

On the development of multi-physics tools for nuclear reactor analysis based on OpenFOAM (R): state of the art, lessons learned and perspectives

Carlo Fiorina

In the last two decades, the use of OpenFOAM as a multi-physics library for nuclear applications has grown from a sporadic use for exploratory studies to a widespread application for the analysis of innovative reactor concepts and highly complex problems. ...

ELSEVIER SCIENCE SA2022

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

Michaël Unser, Thanh-An Michel Pham, Pakshal Narendra Bohra, Jonathan Yuelin Dong

Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems involves the characterization of the posterior distribution of the im ...

2022