Estimation variationnelle robuste de modèles complexes de diffusion en IRM à haute résolution angulaire et tractographie

Haz-Edine Assemlal (1) , David Tschumperlé (2) , Luc Brun (2)

1 GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
2 Equipe Image - Laboratoire GREYC - UMR6072

We present a robust method to retrieve neuronal fibers in human brain white matter from High-Angular Resolution MRI (HARDI datasets). Contrary to classical fiber-tracking techniques done on the traditional 2nd-order tensor model (DTI) which may lead to truncated or biased estimated diffusion directions in case of fiber crossing configurations, we propose here a more complex approach based on a variational estimation of Orientation Diffusion Functions (ODF) modeled with spherical harmonics. This kind of model can correctly retrieve multiple fiber directions corresponding to underlying intravoxel fibers populations. Our technique is able to consider the Rician noise model of the MRI acquisition in order to better estimate the white matter fiber tracks. Results on both synthetic and real human brain white matter HARDI datasets illustrate the effectiveness of the proposed approach.

Mots clés: Rician noise; Variational framework; ODF; fiber-tracking; diffusion MRI

Domaines: Imagerie médicale

Haz-Edine Assemlal, David Tschumperlé, Luc Brun. Estimation variationnelle robuste de modèles complexes de diffusion en IRM à haute résolution angulaire et tractographie. GRETSI, Sep 2007, Troyes, France. pp.5-8. ⟨hal-00329157⟩