eprintid: 10042641
rev_number: 24
eprint_status: archive
userid: 608
dir: disk0/10/04/26/41
datestamp: 2018-02-07 17:19:38
lastmod: 2021-09-19 22:17:53
status_changed: 2018-02-07 17:19:38
type: article
metadata_visibility: show
creators_name: Andersson, JLR
creators_name: Graham, MS
creators_name: Drobnjak, I
creators_name: Zhang, H
creators_name: Campbell, J
title: Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data.
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Diffusion, Dynamic, Movement, Registration, Susceptibility
note: © 2017 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
abstract: Because of their low bandwidth in the phase-encode (PE) direction, the susceptibility-induced off-resonance field causes distortions in echo planar imaging (EPI) images. It is therefore crucial to correct for susceptibility-induced distortions when performing diffusion studies using EPI. The susceptibility-induced field is caused by the object (head) disrupting the field and it is typically assumed that it remains constant within a framework defined by the object, (i.e. it follows the object as it moves in the scanner). However, this is only approximately true. When a non-spherical object rotates around an axis other than that parallel with the magnetic flux (the z-axis) it changes the way it disrupts the field, leading to different distortions. Hence, if using a single field to correct for distortions there will be residual distortions in the volumes where the object orientation is substantially different to that when the field was measured. In this paper we present a post-processing method for estimating the field as it changes with motion during the course of an experiment. It only requires a single measured field and knowledge of the orientation of the subject when that field was acquired. The volume-to-volume changes of the field as a consequence of subject movement are estimated directly from the diffusion data without the need for any additional or special acquisitions. It uses a generative model that predicts how each volume would look predicated on field change and inverts that model to yield an estimate of the field changes. It has been validated on both simulations and experimental data. The results show that we are able to track the field with high accuracy and that we are able to correct the data for the adverse effects of the changing field.
date: 2018-05-01
date_type: published
official_url: https://doi.org/10.1016/j.neuroimage.2017.12.040
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
article_type_text: Journal Article
verified: verified_manual
elements_id: 1520819
doi: 10.1016/j.neuroimage.2017.12.040
pii: S1053-8119(17)31060-1
language_elements: eng
lyricists_name: Drobnjak, Ivana
lyricists_name: Graham, Mark
lyricists_name: Zhang, Hui
lyricists_id: IDROB84
lyricists_id: MGRAH02
lyricists_id: HZHAN50
actors_name: Bracey, Alan
actors_id: ABBRA90
actors_role: owner
full_text_status: public
publication: Neuroimage
volume: 171
pagerange: 277-295
event_location: United States
issn: 1095-9572
citation:        Andersson, JLR;    Graham, MS;    Drobnjak, I;    Zhang, H;    Campbell, J;      (2018)    Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data.                   Neuroimage , 171    pp. 277-295.    10.1016/j.neuroimage.2017.12.040 <https://doi.org/10.1016/j.neuroimage.2017.12.040>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10042641/1/1-s2.0-S1053811917310601-main.pdf