Multi-Dimensional Diffusion MRI Sampling Scheme: B-tensor Design and Accurate Signal Reconstruction

Alice Bates; Alessandro Daducci; Emmanuel Caruyer

Multi-Dimensional Diffusion MRI Sampling Scheme: B-tensor Design and Accurate Signal Reconstruction

Alice Bates ¹ Alessandro Daducci ² Emmanuel Caruyer ³

1 ANU - Australian National University - Department of engineering

2 Department of Computer Science - University of Verona

3 Empenn

INSERM - Institut National de la Santé et de la Recherche Médicale, Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE

Abstract : B-tensor encoding enables the separation of isotropic and anisotropic tensors. However, little consideration has been given as to how to design a b-tensor encoding sampling scheme. In this work, we propose the first 4D basis for representing the diffusion signal acquired with b-tensor encoding. We study the properties of the diffusion signal in this basis to give recommendations for optimally sampling the space of axisymmetric b-tensors. We show, using simulations, that the proposed sampling scheme enables accurate reconstruction of the diffusion signal by expansion in this basis using a clinically feasible number of samples.

Document type :

Conference papers

Domain :

Life Sciences [q-bio] / Neurons and Cognition [q-bio.NC]

Complete list of metadatas

https://www.hal.inserm.fr/inserm-02065830
Contributor : Emmanuel Caruyer <>
Submitted on : Wednesday, March 13, 2019 - 6:59:50 AM
Last modification on : Friday, March 15, 2019 - 1:17:06 AM

bates-daducci-etal-ismrm2019.p...

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