Dataset Information

Slice-level diffusion encoding for motion and distortion correction.

ABSTRACT: Advances in microstructural modelling are leading to growing requirements on diffusion MRI acquisitions, namely sensitivity to smaller structures and better resolution of the geometric orientations. The resulting acquisitions contain highly attenuated images that present particular challenges when there is motion and geometric distortion. This study proposes to address these challenges by breaking with the conventional one-volume-one-encoding paradigm employed in conventional diffusion imaging using single-shot Echo Planar Imaging. By enabling free choice of the diffusion encoding on the slice level, a higher temporal sampling of slices with low b-value can be achieved. These allow more robust motion correction, and in combination with a second reversed phase-encoded echo, also dynamic distortion correction. These proposed advances are validated on phantom and adult experiments and employed in a study of eight foetal subjects. Equivalence in obtained diffusion quantities with the conventional method is demonstrated as well as benefits in distortion and motion correction. The resulting capability can be combined with any acquisition parameters including multiband imaging and allows application to diffusion MRI studies in general.

SUBMITTER: Hutter J

PROVIDER: S-EPMC6191883 | biostudies-other | 2018 Aug

REPOSITORIES: biostudies-other

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Slice-level diffusion encoding for motion and distortion correction.

Hutter Jana J Christiaens Daan J DJ Schneider Torben T Cordero-Grande Lucilio L Slator Paddy J PJ Deprez Maria M Price Anthony N AN Tournier J-Donald JD Rutherford Mary M Hajnal Joseph V JV

Medical image analysis 20180625

Advances in microstructural modelling are leading to growing requirements on diffusion MRI acquisitions, namely sensitivity to smaller structures and better resolution of the geometric orientations. The resulting acquisitions contain highly attenuated images that present particular challenges when there is motion and geometric distortion. This study proposes to address these challenges by breaking with the conventional one-volume-one-encoding paradigm employed in conventional diffusion imaging u ...[more]

PMID: 29966941

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Dataset Information

Slice-level diffusion encoding for motion and distortion correction.

Publications

Slice-level diffusion encoding for motion and distortion correction.

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