dc.contributor.author |
Holdsworth, Samantha |
en |
dc.contributor.author |
Skare, Stefan |
en |
dc.contributor.author |
Newbould, Rexford D |
en |
dc.contributor.author |
Bammer, Roland |
en |
dc.date.accessioned |
2018-11-13T23:35:09Z |
en |
dc.date.issued |
2009-12 |
en |
dc.identifier.issn |
0740-3194 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/44231 |
en |
dc.description.abstract |
Readout segmentation (RS-EPI) has been suggested as a promising variant to echo-planar imaging (EPI) for high-resolution imaging, particularly when combined with parallel imaging. This work details some of the technical aspects of diffusion-weighted (DW)-RS-EPI, outlining a set of reconstruction methods and imaging parameters that can both minimize the scan time and afford high-resolution diffusion imaging with reduced distortions. These methods include an efficient generalized autocalibrating partially parallel acquisition (GRAPPA) calibration for DW-RS-EPI data without scan time penalty, together with a variant for the phase correction of partial Fourier RS-EPI data. In addition, the role of pulsatile and rigid-body brain motion in DW-RS-EPI was assessed. Corrupt DW-RS-EPI data arising from pulsatile nonlinear brain motion had a prevalence of approximately 7% and were robustly identified via k-space entropy metrics. For DW-RS-EPI data corrupted by rigid-body motion, we showed that no blind overlap was required. The robustness of RS-EPI toward phase errors and motion, together with its minimized distortions compared with EPI, enables the acquisition of exquisite 3 T DW images with matrix sizes close to 512(2). |
en |
dc.format.medium |
Print |
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dc.language |
eng |
en |
dc.relation.ispartofseries |
Magnetic resonance in medicine |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.subject |
Brain |
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dc.subject |
Humans |
en |
dc.subject |
Image Interpretation, Computer-Assisted |
en |
dc.subject |
Diffusion Magnetic Resonance Imaging |
en |
dc.subject |
Echo-Planar Imaging |
en |
dc.subject |
Image Enhancement |
en |
dc.subject |
Sensitivity and Specificity |
en |
dc.subject |
Reproducibility of Results |
en |
dc.subject |
Algorithms |
en |
dc.subject |
Pattern Recognition, Automated |
en |
dc.title |
Robust GRAPPA-accelerated diffusion-weighted readout-segmented (RS)-EPI. |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1002/mrm.22122 |
en |
pubs.issue |
6 |
en |
pubs.begin-page |
1629 |
en |
pubs.volume |
62 |
en |
dc.rights.holder |
Copyright: The author |
en |
dc.identifier.pmid |
19859974 |
en |
pubs.end-page |
1640 |
en |
pubs.publication-status |
Published |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Research Support, Non-U.S. Gov't |
en |
pubs.subtype |
research-article |
en |
pubs.subtype |
Journal Article |
en |
pubs.subtype |
Research Support, N.I.H., Extramural |
en |
pubs.elements-id |
683334 |
en |
pubs.org-id |
Medical and Health Sciences |
en |
pubs.org-id |
Medical Sciences |
en |
pubs.org-id |
Anatomy and Medical Imaging |
en |
dc.identifier.eissn |
1522-2594 |
en |
pubs.record-created-at-source-date |
2009-11-30 |
en |
pubs.dimensions-id |
19859974 |
en |