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Publication Detail
Current Applications and Future Promises of Machine Learning in Diffusion MRI
  • Publication Type:
    Conference
  • Authors:
    Ravi D, Ghavami N, Alexander DC, Ianus A
  • Publisher:
    Springer
  • Publication date:
    03/05/2019
  • Pagination:
    105, 121
  • Published proceedings:
    Mathematics and Visualization
  • Issue:
    226249
  • Status:
    Published
  • Name of conference:
    Workshop on Computational Diffusion MRI (CDMRI’18) - MICCAI 2018 Workshop
  • Conference place:
    Granada, Spain
  • Conference start date:
    16/09/2018
  • Conference finish date:
    20/09/2018
  • Print ISSN:
    1612-3786
Abstract
© 2019, Springer Nature Switzerland AG. 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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