Pieciak, T, Afzali, M, Bogusz, F et al. (2 more authors) (2021) Q-Space Quantitative Diffusion MRI Measures Using a Stretched-Exponential Representation. In: Computational Diffusion MRI: International MICCAI Workshop, Lima, Peru, October 2020. Computational Diffusion MRI: International MICCAI Workshop 2020, 04 Oct 2020 Springer , pp. 121-133. ISBN 9783030730178
Abstract
Diffusion magnetic resonance imaging (dMRI) is a relatively modern technique used to study tissue microstructure in a non-invasive way. Non-Gaussian diffusion representation is related to the restricted diffusion and can provide information about the underlying tissue properties. In this paper, we analytically derive nth order statistics of the signal considering a stretched-exponential representation of the diffusion. Then, we retrieve the Q-space quantitative measures such as the Return-To-the-Origin Probability (RTOP), Q-space mean square displacement (QMSD), Q-space mean fourth-order displacement (QMFD). The stretched-exponential representation enables the handling of the diffusion contributions from a higher b-value regime under a non-Gaussian assumption, which can be useful in diagnosing or prognosis of neurodegenerative diseases in the early stages. Numerical implementation of the method is freely available at https://github.com/TPieciak/Stretched.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is an author produced version of a conference paper published in Computational Diffusion MRI: International MICCAI Workshop, Lima, Peru, October 2020. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Biomedical Imaging Science Dept (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jun 2022 14:42 |
Last Modified: | 30 Sep 2022 00:32 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-030-73018-5_10 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187977 |