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Current Applications and Future Promises of Machine Learning in Diffusion MRI

Ravi, D; Ghavami, N; Alexander, DC; Ianus, A; (2019) Current Applications and Future Promises of Machine Learning in Diffusion MRI. In: Frangi, Alejandro and Alberola-Lopez, Carlos and Porras, Antonio R, (eds.) Proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018). (pp. pp. 105-121). Springer: Cham, Switzerland. Green open access

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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 is used in many applications both in the brain and other parts of the body such as the breast and prostate, and novel computational 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 which machine learning and deep 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.

Type: Proceedings paper
Title: Current Applications and Future Promises of Machine Learning in Diffusion MRI
Event: 21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2018), 16-20 September 2018, Grenada, Spain
ISBN-13: 978-3-030-05830-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-05831-9_9
Publisher version: https://doi.org/10.1007/978-3-030-05831-9
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Diffusion-Weighted, MRI, Machine Learning, Deep Learning
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10077838
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