Bousquet J.,Montpellier University |
Bourquin C.,Region Languedoc Roussillon |
Auge P.,Montpellier University |
Domy P.,Montpellier University |
And 168 more authors.
European Geriatric Medicine | Year: 2014
The Région Languedoc-Roussillon is the umbrella organisation for an interconnected and integrated project on AHA covering the 3 pillars of the European Innovation Partnership on Active and Healthy Ageing. All sub-activities (A1: electronic pharmaceutical file, A2: falls prevention initiative, A3: frailty, B3: chronic respiratory diseases, chronic diseases with comorbidities, oral health and hepatitis virus C chronic infection, C2 and D4 active and independent living and handicap) are included in MACVIA-LR that has a strong political commitment and includes all stakeholders (public, private, patients, policy makers). It is one of the Reference Sites of the European Innovation Partnership on Active and Healthy Ageing built around chronic diseases, ageing and handicap. The framework of MACVIA-LR has the vision that the prevention and management of CDs is essential for AHA promotion and for the reduction of handicap. The main objective of MACVIA-LR is to develop innovative solutions for a network of Living Labs in order to improve the care of patients affected by CDs in the Languedoc-Roussillon area and to disseminate the innovation. © 2014 Published by Elsevier Masson SAS.
Tauber C.,French Institute of Health and Medical Research |
Stute S.,IMNC |
Chau M.,ASA Advanced Solutions Accelerator |
Spiteri P.,CNRS Toulouse Institute in Information Technology |
And 3 more authors.
Physics in Medicine and Biology | Year: 2011
Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging. © 2011 Institute of Physics and Engineering in Medicine.