PARIETAL - 2013 - Annual activity report

PARIETAL

PARIETAL - 2013

Project-Team Parietal

Members

Overall Objectives

Highlights of the Year

Research Program

Human neuroimaging data and its use
High-field MRI
Technical challenges for the analysis of neuroimaging data

Application Domains

Inverse problems in Neuroimaging
Multivariate decompositions
Covariance estimation

Software and Platforms

Scikit learn
Nilearn
Mayavi
Nipy
MedInria
PyHRF

New Results

Deformable Template estimation for joint anatomical and functional brain images
Randomized parcellation-based inference
Group-level impacts of within- and between-subject hemodynamic variability in fMRI
Mapping cognitive ontologies to and from the brain
Implications of Inconsistencies between fMRI and dMRI on Multimodal Connectivity Estimation
Extracting brain regions from rest fMRI with Total-Variation constrained dictionary learning
Cohort-level brain mapping: learning cognitive atoms to single out specialized regions
Identifying predictive regions from fMRI with TV- $ℓ$ 1 prior
Second order scattering descriptors predict fMRI activity due to visual textures
Bayesian Joint Detection-Estimation of cerebral vasoreactivity from ASL fMRI data

Partnerships and Cooperations

Regional Initiatives
National Initiatives
European Initiatives
International Initiatives
International Research Visitors

Dissemination

Scientific Animation
Teaching - Supervision - Juries
Popularization

Bibliography

Major publications
Publications of the year
References in notes

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Section: Software and Platforms

MedInria

Participants : Pierre Fillard [correspondant] , Sergio Medina, Viviana Siless.

MedInria is a free collection of softwares developed within the Asclepios, Athena and Visages research projects. It aims at providing to clinicians state-of-the-art algorithms dedicated to medical image processing and visualization. Efforts have been made to simplify the user interface, while keeping high-level algorithms. MedInria is available for Microsoft windows XP/Vista, Linux Fedora Core, MacOSX, and is fully multithreaded.

See also the web page http://med.inria.fr/ .

Version: 2.0

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