000267814 001__ 267814
000267814 005__ 20190701163400.0
000267814 0247_ $$2doi$$a10.1002/nbm.3805
000267814 02470 $$2PMID$$a29134716
000267814 037__ $$aARTICLE
000267814 245__ $$aAdvances in computational and statistical diffusion MRI
000267814 260__ $$c2019
000267814 269__ $$a2019
000267814 336__ $$aReviews
000267814 520__ $$aComputational 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.
000267814 6531_ $$aCIBM-AIT
000267814 700__ $$aO'Donnell, Lauren J.
000267814 700__ $$aDaducci, Alessandro
000267814 700__ $$aWassermann, Demian
000267814 700__ $$aLenglet, Christophe
000267814 773__ $$tNMR in Biomedicine$$j32$$k4$$qe3805
000267814 8560_ $$fvalerie.charbonnier@epfl.ch
000267814 909C0 $$zPasquier, Simon$$xU12623$$pCIBM$$mrolf.gruetter@epfl.ch$$0252477
000267814 909CO $$ooai:infoscience.epfl.ch:267814$$particle$$preview$$pSB
000267814 960__ $$arolf.gruetter@epfl.ch
000267814 961__ $$avalerie.charbonnier@epfl.ch
000267814 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000267814 980__ $$aARTICLE
000267814 981__ $$aoverwrite