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Hybrid prospective and retrospective head motion correction to mitigate cross‐calibration errors
Author(s) -
Aksoy Murat,
Forman Christoph,
Straka Matus,
Çukur Tolga,
Hornegger Joachim,
Bammer Roland
Publication year - 2012
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.23101
Subject(s) - computer science , calibration , computer vision , artificial intelligence , scanner , tracking (education) , match moving , image quality , motion (physics) , mathematics , statistics , psychology , pedagogy , image (mathematics)
Utilization of external motion tracking devices is an emerging technology in head motion correction for MRI. However, cross‐calibration between the reference frames of the external tracking device and the MRI scanner can be tedious and remains a challenge in practical applications. In this study, we present two hybrid methods, both of which combine prospective, optical‐based motion correction with retrospective entropy‐based autofocusing to remove residual motion artifacts. Our results revealed that in the presence of cross‐calibration errors between the optical tracking device and the MR scanner, application of retrospective correction on prospectively corrected data significantly improves image quality. As a result of this hybrid prospective and retrospective motion correction approach, the requirement for a high‐quality calibration scan can be significantly relaxed, even to the extent that it is possible to perform external prospective motion tracking without any prior cross‐calibration step if a crude approximation of cross‐calibration matrix exists. Moreover, the motion tracking system, which is used to reduce the dimensionality of the autofocusing problem, benefits the retrospective approach at the same time. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.