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PROMO: Real‐time prospective motion correction in MRI using image‐based tracking
Open accessAbstract
Artifacts caused by patient motion during scanning remain a serious problem in most MRI applications. The prospective motion correction technique attempts to address this problem at its source by keeping the measurement coordinate system fixed with respect to the patient throughout the entire scan process. In this study, a new image‐based approach for prospective motion correction is described, which utilizes three orthogonal two‐dimensional spiral navigator acquisitions, along with a flexible image‐based tracking method based on the extended Kalman filter algorithm for online motion measurement. The spiral navigator/extended Kalman filter framework offers the advantages of image‐domain tracking within patient‐specific regions‐of‐interest and reduced sensitivity to off‐resonance‐induced corruption of rigid‐body motion estimates. The performance of the method was tested using offline computer simulations and online in vivo head motion experiments. In vivo validation results covering a broad range of staged head motions indicate a steady‐state error of less than 10% of the motion magnitude, even for large compound motions that included rotations over 15 deg. A preliminary in vivo application in three‐dimensional inversion recovery spoiled gradient echo (IR‐SPGR) and three‐dimensional fast spin echo (FSE) sequences demonstrates the effectiveness of the spiral navigator/extended Kalman filter framework for correcting three‐dimensional rigid‐body head motion artifacts prospectively in high‐resolution three‐dimensional MRI scans. Magn Reson Med, 2010. © 2009 Wiley‐Liss, Inc.
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Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Cited by
Yan, C.-G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., Li, Q., Zuo, X.-N., Castellanos, F. X., & Milham, M. P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.004 · Cited by 1,461
Uğurbil, K., Xu, J., Auerbach, E. J., Moeller, S., Vu, A. T., Duarte-Carvajalino, J. M., Lenglet, C., Wu, X., Schmitter, S., Van de Moortele, P. F., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.012 · Cited by 812
Methods for cleaning the BOLD fMRI signal
Caballero-Gaudes, C., & Reynolds, R. C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.018 · Cited by 542
Head motion during MRI acquisition reduces gray matter volume and thickness estimates
Reuter, M., Tisdall, M. D., Qureshi, A., Buckner, R. L., van der Kouwe, A. J. W., & Fischl, B. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.006 · Cited by 457
Valk, S. L., Bernhardt, B. C., Trautwein, F.-M., Böckler, A., Kanske, P., Guizard, N., Collins, D. L., & Singer, T. (2017) · Science Advances · doi:10.1126/sciadv.1700489 · Cited by 264
Metadata
- Authors
- White, N., Roddey, C., Shankaranarayanan, A., Han, E., Rettmann, D., Santos, J., Kuperman, J., & Dale, A.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2009-12-21
- Volume
- 63
- Issue
- 1
- Pages
- 91-105
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W1986218154
- Cited by
- 376
- References
- 1
- FWCI
- 10.80
- Type
- journal article
- Language
- en
- Open access
- bronze
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