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.
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https://www.hal.inserm.fr/inserm-02065830
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Submitted on : Wednesday, March 13, 2019 - 6:59:50 AM
Last modification on : Friday, September 13, 2019 - 9:50:02 AM
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  • HAL Id : inserm-02065830, version 1

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Alice Bates, Alessandro Daducci, Emmanuel Caruyer. Multi-Dimensional Diffusion MRI Sampling Scheme: B-tensor Design and Accurate Signal Reconstruction. ISMRM 2019 - 27th Annual Meeting & Exhibition, May 2019, Montréal, Canada. pp.1-4. ⟨inserm-02065830⟩

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