Literature DB >> 30821010

Markerless high-frequency prospective motion correction for neuroanatomical MRI.

Robert Frost1,2, Paul Wighton1, F Işık Karahanoğlu1,2, Richard L Robertson3, P Ellen Grant3,4, Bruce Fischl1,2,5, M Dylan Tisdall6, André van der Kouwe1,2.   

Abstract

PURPOSE: To integrate markerless head motion tracking with prospectively corrected neuroanatomical MRI sequences and to investigate high-frequency motion correction during imaging echo trains.
METHODS: A commercial 3D surface tracking system, which estimates head motion by registering point cloud reconstructions of the face, was used to adapt the imaging FOV based on head movement during MPRAGE and T2 SPACE (3D variable flip-angle turbo spin-echo) sequences. The FOV position and orientation were updated every 6 lines of k-space (< 50 ms) to enable "within-echo-train" prospective motion correction (PMC). Comparisons were made with scans using "before-echo-train" PMC, in which the FOV was updated only once per TR, before the start of each echo train (ET). Continuous-motion experiments with phantoms and in vivo were used to compare these high-frequency and low-frequency correction strategies. MPRAGE images were processed with FreeSurfer to compare estimates of brain structure volumes and cortical thickness in scans with different PMC.
RESULTS: The median absolute pose differences between markerless tracking and MR image registration were 0.07/0.26/0.15 mm for x/y/z translation and 0.06º/0.02º/0.12° for rotation about x/y/z. The PMC with markerless tracking substantially reduced motion artifacts. The continuous-motion experiments showed that within-ET PMC, which minimizes FOV encoding errors during ETs that last over 1 second, reduces artifacts compared with before-ET PMC. T2 SPACE was found to be more sensitive to motion during ETs than MPRAGE. FreeSurfer morphometry estimates from within-ET PMC MPRAGE images were the most accurate.
CONCLUSION: Markerless head tracking can be used for PMC, and high-frequency within-ET PMC can reduce sensitivity to motion during long imaging ETs.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  brain morphometry; high-frequency prospective motion correction; markerless motion tracking; real-time motion correction

Mesh:

Year:  2019        PMID: 30821010      PMCID: PMC6491242          DOI: 10.1002/mrm.27705

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  42 in total

1.  Rapid three-dimensional T1-weighted MR imaging with the MP-RAGE sequence.

Authors:  J P Mugler; J R Brookeman
Journal:  J Magn Reson Imaging       Date:  1991 Sep-Oct       Impact factor: 4.813

2.  Cortical surface-based analysis. I. Segmentation and surface reconstruction.

Authors:  A M Dale; B Fischl; M I Sereno
Journal:  Neuroimage       Date:  1999-02       Impact factor: 6.556

3.  Avoiding asymmetry-induced bias in longitudinal image processing.

Authors:  Martin Reuter; Bruce Fischl
Journal:  Neuroimage       Date:  2011-03-03       Impact factor: 6.556

4.  Properties of a 2D fat navigator for prospective image domain correction of nodding motion in brain MRI.

Authors:  Stefan Skare; Axel Hartwig; Magnus Mårtensson; Enrico Avventi; Mathias Engström
Journal:  Magn Reson Med       Date:  2014-04-14       Impact factor: 4.668

5.  Prospective motion correction with NMR markers using only native sequence elements.

Authors:  Alexander Aranovitch; Maximilian Haeberlin; Simon Gross; Benjamin E Dietrich; Bertram J Wilm; David O Brunner; Thomas Schmid; Roger Luechinger; Klaas P Pruessmann
Journal:  Magn Reson Med       Date:  2017-08-24       Impact factor: 4.668

6.  Real-time optical motion correction for diffusion tensor imaging.

Authors:  Murat Aksoy; Christoph Forman; Matus Straka; Stefan Skare; Samantha Holdsworth; Joachim Hornegger; Roland Bammer
Journal:  Magn Reson Med       Date:  2011-03-22       Impact factor: 4.668

7.  TArgeted Motion Estimation and Reduction (TAMER): Data Consistency Based Motion Mitigation for MRI Using a Reduced Model Joint Optimization.

Authors:  Melissa W Haskell; Stephen F Cauley; Lawrence L Wald
Journal:  IEEE Trans Med Imaging       Date:  2018-05       Impact factor: 10.048

8.  Spurious group differences due to head motion in a diffusion MRI study.

Authors:  Anastasia Yendiki; Kami Koldewyn; Sita Kakunoori; Nancy Kanwisher; Bruce Fischl
Journal:  Neuroimage       Date:  2013-11-21       Impact factor: 6.556

9.  Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI.

Authors:  Aaron Alexander-Bloch; Liv Clasen; Michael Stockman; Lisa Ronan; Francois Lalonde; Jay Giedd; Armin Raznahan
Journal:  Hum Brain Mapp       Date:  2016-03-23       Impact factor: 5.038

10.  Individual differences in impulsivity predict head motion during magnetic resonance imaging.

Authors:  Xiang-Zhen Kong; Zonglei Zhen; Xueting Li; Huan-Hua Lu; Ruosi Wang; Ling Liu; Yong He; Yufeng Zang; Jia Liu
Journal:  PLoS One       Date:  2014-08-22       Impact factor: 3.240

View more
  13 in total

1.  Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging.

Authors:  Ayush Singh; Seyed Sadegh Mohseni Salehi; Ali Gholipour
Journal:  IEEE Trans Med Imaging       Date:  2020-10-28       Impact factor: 10.048

2.  Retrospective correction of head motion using measurements from an electromagnetic tracker.

Authors:  Onur Afacan; Tess E Wallace; Simon K Warfield
Journal:  Magn Reson Med       Date:  2019-08-10       Impact factor: 4.668

3.  Toward "plug and play" prospective motion correction for MRI by combining observations of the time varying gradient and static vector fields.

Authors:  Adam van Niekerk; Andre van der Kouwe; Ernesta Meintjes
Journal:  Magn Reson Med       Date:  2019-05-07       Impact factor: 4.668

4.  Comparison of prospective and retrospective motion correction in 3D-encoded neuroanatomical MRI.

Authors:  Jakob M Slipsager; Stefan L Glimberg; Liselotte Højgaard; Rasmus R Paulsen; Paul Wighton; M Dylan Tisdall; Camilo Jaimes; Borjan A Gagoski; P Ellen Grant; André van der Kouwe; Oline V Olesen; Robert Frost
Journal:  Magn Reson Med       Date:  2021-09-07       Impact factor: 4.668

5.  Automated detection and reacquisition of motion-degraded images in fetal HASTE imaging at 3 T.

Authors:  Borjan Gagoski; Junshen Xu; Paul Wighton; M Dylan Tisdall; Robert Frost; Wei-Ching Lo; Polina Golland; Andre van der Kouwe; Elfar Adalsteinsson; P Ellen Grant
Journal:  Magn Reson Med       Date:  2021-12-10       Impact factor: 3.737

6.  Self-Navigated Three-Dimensional Ultrashort Echo Time Technique for Motion-Corrected Skull MRI.

Authors:  Hyunyeol Lee; Xia Zhao; Hee Kwon Song; Felix W Wehrli
Journal:  IEEE Trans Med Imaging       Date:  2020-03-04       Impact factor: 10.048

7.  A Combined Deep-Learning and Lattice Boltzmann Model for Segmentation of the Hippocampus in MRI.

Authors:  Yingqian Liu; Zhuangzhi Yan
Journal:  Sensors (Basel)       Date:  2020-06-28       Impact factor: 3.576

8.  Concept for Markerless 6D Tracking Employing Volumetric Optical Coherence Tomography.

Authors:  Matthias Schlüter; Lukas Glandorf; Martin Gromniak; Thore Saathoff; Alexander Schlaefer
Journal:  Sensors (Basel)       Date:  2020-05-08       Impact factor: 3.576

9.  Improved motion correction of submillimetre 7T fMRI time series with Boundary-Based Registration (BBR).

Authors:  Pei Huang; Johan D Carlin; Richard N Henson; Marta M Correia
Journal:  Neuroimage       Date:  2020-01-18       Impact factor: 6.556

10.  Probing in vivo cortical myeloarchitecture in humans via line-scan diffusion acquisitions at 7 T with 250-500 micron radial resolution.

Authors:  Mukund Balasubramanian; Robert V Mulkern; Jeffrey J Neil; Stephan E Maier; Jonathan R Polimeni
Journal:  Magn Reson Med       Date:  2020-08-01       Impact factor: 4.668

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.