Published March 30, 2011
| Version v1
Conference paper
Spherical Polar Fourier EAP and ODF Reconstruction via Compressed Sensing in Diffusion MRI
Contributors
Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Brain imaging (LIAMA) ; Laboratoire Franco-Chinois d'Informatique, d'Automatique et de Mathématiques Appliquées (LIAMA) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Chinese Academy of Sciences [Changchun Branch] (CAS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institute of Automation - Chinese Academy of Sciences-Centre National de la Recherche Scientifique (CNRS)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Chinese Academy of Sciences [Changchun Branch] (CAS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institute of Automation - Chinese Academy of Sciences-Centre National de la Recherche Scientifique (CNRS)
Description
In diffusion magnetic resonance imaging (dMRI), the Ensemble Average Propagator (EAP), also known as the propagator, describes completely the water molecule diffusion in the brain white matter without any prior knowledge about the tissue shape. In this paper, we describe a new and efficient method to accurately reconstruct the EAP in terms of the Spherical Polar Fourier (SPF) basis from very few diffusion weighted magnetic resonance images (DW-MRI). This approach nicely exploits the duality between SPF and a closely related basis in which one can respectively represent the EAP and the diffusion signal using the same coefficients, and efficiently combines it to the recent acquisition and reconstruction technique called Compressed Sensing (CS). Our work provides an efficient analytical solution to estimate, from few measurements, the diffusion propagator at any radius. We also provide a new analytical solution to extract an important feature characterising the tissue microstructure: the Orientation Distribution Function (ODF). We illustrate and prove the effectiveness of our method in reconstructing the propagator and the ODF on both noisy multiple q-shell synthetic and phantom data.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/inria-00585694
- URN
- urn:oai:HAL:inria-00585694v1
Origin repository
- Origin repository
- UNICA