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2019 | OriginalPaper | Chapter

Current Applications and Future Promises of Machine Learning in Diffusion MRI

Authors : Daniele Ravi, Nooshin Ghavami, Daniel C. Alexander, Andrada Ianus

Published in: Computational Diffusion MRI

Publisher: Springer International Publishing

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Abstract

Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) explores the random motion of diffusing water molecules in biological tissue and can provide information on the tissue structure at a microscopic scale. DW-MRI in used in many applications both in the brain and other parts of the body such as the breast and prostate, and novelcomputational methods are at the core of advancements in DW-MRI, both in terms of research and its clinical translation. This article reviews the ways in whichmachine learning anddeep learning is currently applied in DW-MRI. We will also discuss the more traditional methods used for processing diffusion MRI and the potential of deep learning in augmenting these existing methods in the future.

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Title: Current Applications and Future Promises of Machine Learning in Diffusion MRI
Authors: Daniele Ravi
Nooshin Ghavami
Daniel C. Alexander
Andrada Ianus
Publisher: Springer International Publishing
Book: Computational Diffusion MRI
Print ISBN: 978-3-030-05830-2

Electronic ISBN: 978-3-030-05831-9

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-05831-9_9

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