Advances in computational and statistical diffusion MRI

Lauren J. O'Donnell, Alessandro Daducci, Demian Wassermann, Christophe Lenglet

Research output: Contribution to journalReview article

4 Citations (Scopus)

Abstract

Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotropies or apparent axon diameters, whole-brain connectivity information that describes the brain's wiring diagram and population-based studies in health and disease. Many of the diffusion MRI analyses performed today were not possible five, ten or twenty years ago, due to the requirements for large amounts of computer memory or processor time. In addition, mathematical frameworks had to be developed or adapted from other fields to create new ways to analyze diffusion MRI data. The purpose of this review is to highlight recent computational and statistical advances in diffusion MRI and to put these advances into context by comparison with the more traditional computational methods that are in popular clinical and scientific use. We aim to provide a high-level overview of interest to diffusion MRI researchers, with a more in-depth treatment to illustrate selected computational advances.

Original languageEnglish (US)
Article numbere3805
JournalNMR in biomedicine
Volume32
Issue number4
DOIs
StatePublished - Jan 1 2019

Fingerprint

Diffusion Magnetic Resonance Imaging
Magnetic resonance
Imaging techniques
Brain
Computational methods
Anisotropy
Electric wiring
Axons
Research Personnel
Health
Data storage equipment
Microstructure
Population

Keywords

  • diffusion MRI
  • registration
  • statistics
  • tractography

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

Cite this

Advances in computational and statistical diffusion MRI. / O'Donnell, Lauren J.; Daducci, Alessandro; Wassermann, Demian; Lenglet, Christophe.

In: NMR in biomedicine, Vol. 32, No. 4, e3805, 01.01.2019.

Research output: Contribution to journalReview article

O'Donnell, Lauren J. ; Daducci, Alessandro ; Wassermann, Demian ; Lenglet, Christophe. / Advances in computational and statistical diffusion MRI. In: NMR in biomedicine. 2019 ; Vol. 32, No. 4.
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