FBRAIN
Computational Anatomy of Fetal Brain
| Coordinatore | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
| Nazionalità Coordinatore | France [FR] |
| Totale costo | 753˙393 € |
| EC contributo | 753˙393 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2007-StG |
| Funding Scheme | ERC-SG |
| Anno di inizio | 2008 |
| Periodo (anno-mese-giorno) | 2008-09-01 - 2013-08-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
FR (PARIS) | hostInstitution | 0.00 |
| 2 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
FR (PARIS) | hostInstitution | 0.00 |
Mappa
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Obiettivo del progetto (Objective)
'Studies about brain maturation aim at providing a better understanding of brain development and links between brain changes and cognitive development. Such studies are of great interest for diagnosis help and clinical course of development and treatment of illnesses. Several teams have begun to make 3D maps of developing brain structures from children to young adults. However, working out the development of fetal and neonatal brain remains an open issue. This project aims at jumping over several theoretical and practical barriers and at going beyond the formal description of the brain maturation thanks to the development of a realistic numerical model of brain aging. In this context, Magnetic Resonance (MR) imaging is a fundamental tool to study structural brain development across age group. We will rely on new image processing tools combining morphological information provided by T2-weighted MR images and diffusion information (degree of myelination and fiber orientation) given by diffusion tensor imaging (DTI). The joint analysis of these anatomical features will stress the generic maturation of normal fetal brain. We will first rely on mathematical models to allow reconstruction of high resolution 3D MR images in order to extract relevant features of brain maturation. The results issued from this first step will be used to build statistical atlases and to characterize the neuroanatomical differences between a reference group and the population under investigation. From a methodological point of view, our approach relies on an interdisciplinary research framework aiming at combining medical research to neuroimaging, image processing, statistical modelling and computer science. The robust characterization of the anatomical features of fetal brain and the development of a realistic model of brain maturation from biological concepts will come out from the strong interactions between these different research fields.'