Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences
Diffusion-weighted imaging (DWI) is known to be prone to motion artifacts originating from subject movement, cardiac pulsation and breathing. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which invo...
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doaj-8570d15f6d3045cfa04bc537cb793ca52020-11-24T21:00:23ZengFrontiers Media S.A.Frontiers in Neurology1664-22952014-12-01510.3389/fneur.2014.00240105302Subject-Motion Correction in HARDI Acquisitions: Choices and ConsequencesShireen Y. Elhabian0Shireen Y. Elhabian1Yaniv eGur2Clement eVachet3Joseph ePiven4Martin Andreas Styner5Martin Andreas Styner6Ilana R Leppert7Bruce ePike8Bruce ePike9Guido eGerig10Scientific Computing and Imaging Institute, University of UtahCairo UniversityScientific Computing and Imaging Institute, University of UtahScientific Computing and Imaging Institute, University of UtahDept. of Psychiatry, University of North CarolinaDept. of Psychiatry, University of North CarolinaDept. of Computer Science, University of North CarolinaDept. of Neurology and Neurosurgery, Montréal Neurological Institute, MontréalDept. of Neurology and Neurosurgery, Montréal Neurological Institute, MontréalDept. of Radiology, University of CalgaryScientific Computing and Imaging Institute, University of UtahDiffusion-weighted imaging (DWI) is known to be prone to motion artifacts originating from subject movement, cardiac pulsation and breathing. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involve simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. Whereas post-acquisition motion correction is widely performed, the effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk to introduce confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on studying the impact of motion correction using four different metrics which quantify (1) similarity of fiber orientation distribution functions, (2) deviation of local fiber orientations, (3) global brain connectivity, and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad-hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00240/fullHARDIMotion Correctionsubject motionfiber orientationsorientation distribution functionstractography comparison |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shireen Y. Elhabian Shireen Y. Elhabian Yaniv eGur Clement eVachet Joseph ePiven Martin Andreas Styner Martin Andreas Styner Ilana R Leppert Bruce ePike Bruce ePike Guido eGerig |
spellingShingle |
Shireen Y. Elhabian Shireen Y. Elhabian Yaniv eGur Clement eVachet Joseph ePiven Martin Andreas Styner Martin Andreas Styner Ilana R Leppert Bruce ePike Bruce ePike Guido eGerig Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences Frontiers in Neurology HARDI Motion Correction subject motion fiber orientations orientation distribution functions tractography comparison |
author_facet |
Shireen Y. Elhabian Shireen Y. Elhabian Yaniv eGur Clement eVachet Joseph ePiven Martin Andreas Styner Martin Andreas Styner Ilana R Leppert Bruce ePike Bruce ePike Guido eGerig |
author_sort |
Shireen Y. Elhabian |
title |
Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences |
title_short |
Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences |
title_full |
Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences |
title_fullStr |
Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences |
title_full_unstemmed |
Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences |
title_sort |
subject-motion correction in hardi acquisitions: choices and consequences |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neurology |
issn |
1664-2295 |
publishDate |
2014-12-01 |
description |
Diffusion-weighted imaging (DWI) is known to be prone to motion artifacts originating from subject movement, cardiac pulsation and breathing. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involve simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. Whereas post-acquisition motion correction is widely performed, the effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk to introduce confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on studying the impact of motion correction using four different metrics which quantify (1) similarity of fiber orientation distribution functions, (2) deviation of local fiber orientations, (3) global brain connectivity, and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad-hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted. |
topic |
HARDI Motion Correction subject motion fiber orientations orientation distribution functions tractography comparison |
url |
http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00240/full |
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