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In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast is vastly different in different volumes. In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.

Original publication

DOI

10.1016/j.neuroimage.2015.10.019

Type

Journal article

Journal

Neuroimage

Publication Date

15/01/2016

Volume

125

Pages

1063 - 1078

Keywords

Diffusion, Eddy current, Movement, Registration, Susceptibility, Algorithms, Artifacts, Diffusion Magnetic Resonance Imaging, Humans, Image Interpretation, Computer-Assisted, Movement