Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement

By Jesper L. R. Andersson, Mark S. Graham, Ivana Drobnjak, Hui Zhang, Nicola Filippini, Matteo Bastiani. NeuroImage, 2017

366 citations recorded by the source corpus.

ABSTRACT Most motion correction methods work by aligning a set of volumes together, or to a volume that represents a reference location. These are based on an implicit assumption that the subject remains motionless during the several seconds it takes to acquire all slices in a volume, and that any movement occurs in the brief moment between acquiring the last slice of one volume and the first slice of the next. This is clearly an approximation that can be more or less good depending on how long it takes to acquire one volume and in how rapidly the subject moves. In this paper we present a method that increases the temporal resolution of the motion correction by modelling movement as a piecewise continous function over time. This intra‐volume movement correction is implemented within a previously presented framework that simultaneously estimates distortions, movement and movement‐induced signal dropout. We validate the method on highly realistic simulated data containing all of these effects. It is demonstrated that we can estimate the true movement with high accuracy, and that scalar parameters derived from the data, such as fractional anisotropy, are estimated with greater fidelity when data has been corrected for intra‐volume movement. Importantly, we also show that the difference in fidelity between data affected by different amounts of movement is much reduced when taking intra‐volume movement into account. Additional validation was performed on data from a healthy volunteer scanned when lying still and when performing deliberate movements. We show an increased correspondence between the “still” and the “movement” data when the latter is corrected for intra‐volume movement. Finally we demonstrate a big reduction in the telltale signs of intra‐volume movement in data acquired on elderly subjects. HighlightsWe introduce a method to correct for intra‐volume movement into an existing framework for movement and distortion correction.It has been validated on realistic simulated data and on experimental data with deliberate movement.The results indicate that one can reliably reverse the adverse effects of intra‐volume movement.

Subfields: Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/3a3646addd3493f9c63f72ee9001885e5152639c

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In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction (2018, background): “…metrics might indicate an outlier but if EDDY has been run with outlier replacement (Andersson et al., 2016), correction for within volume movement (Andersson et al., 2017) and susceptibility-by-movement correction (Andersson et al., 2018) it may have been able to correct for the effects of…”
The impact of T1 vs EPI spatial normalization templates for fMRI data analyses (2017, background): “And finally, there are also approaches which jointly estimate multiple factors such as distortion correction and movement interactions or EPI Nyquist ghost effects [Andersson et al., 2017; Xie et al., 2017].”
Decomposing the role of alpha oscillations during brain maturation (2020, unknown): “1 (Smith, 2002) and state-of-the-art correction for eddy current-induced distortions in-scanner head motion (Andersson et al., 2017; Andersson, Graham, Zsoldos, & Sotiropoulos, 2016; Andersson & Sotiropoulos, 2016).”