Using 3D-SHORE and MAP-MRI to Obtain Both Tractography and Microstructural Constrast from a Clinical DMRI Acquisition
- Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Department of Computer Science [Verona] (UNIVR | DI) ; Università degli studi di Verona = University of Verona (UNIVR)
- Sherbrooke Connectivity Imaging Lab [Sherbrooke] (SCIL) ; Département d'informatique [Sherbrooke] (UdeS) ; Faculté des sciences [Sherbrooke] (UdeS) ; Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS)-Faculté des sciences [Sherbrooke] (UdeS) ; Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS)
- ANR-13-MONU-0009,MOSIFAH,Modélisation et simulation multimodales et multiéchelles de l'architecture des fibres myocardiques du cœur humain(2013)
Description
Diffusion MRI (dMRI) is used to characterize the directional-ity and microstructural properties of brain white matter (WM) by measuring the diffusivity of water molecules. In clinical practice the number of dMRI samples that can be obtained is limited, and one often uses short scanning protocols that acquire just 32 to 64 different gradient directions using a single gradient strength (b-value). Such 'single shell' scanning protocols restrict one to use methods that have assumptions on the radial decay of the dMRI signal over different b-values, which introduces estimation biases. In this work we show, that by simply spreading the same number of samples over multiple b-values (i.e. multi-shell) we can accurately estimate both the WM directionality using 3D-SHORE and characterize the radially dependent diffusion microstructure measures using MAP-MRI. We validate our approach by undersampling both noisy synthetic and human brain data of the Human Connectome Project, proving this approach is well-suited for clinical applications.
Abstract
International audience
Additional details
- URL
- https://hal.inria.fr/hal-01140011
- URN
- urn:oai:HAL:hal-01140011v1
- Origin repository
- UNICA