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Adaptive retrospective correction of motion artifacts in cranial MRI with multicoil three‐dimensional radial acquisitions
Author(s) -
Anderson Ashley G.,
Velikina Julia,
Block Walter,
Wieben Oliver,
Samsonov Alexey
Publication year - 2013
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.24348
Subject(s) - computer science , computer vision , artificial intelligence , motion compensation , motion (physics) , image quality , motion estimation , flexibility (engineering) , undersampling , projection (relational algebra) , sampling (signal processing) , real time mri , a priori and a posteriori , magnetic resonance imaging , image (mathematics) , algorithm , mathematics , radiology , medicine , philosophy , statistics , filter (signal processing) , epistemology
Despite reduction in imaging times through improved hardware and rapid acquisition schemes, motion artifacts can compromise image quality in magnetic resonance imaging, especially in three‐dimensional imaging with its prolonged scan durations. Direct extension of most state‐of‐the‐art two‐dimensional rigid body motion compensation techniques to the three‐dimensional case is often challenging or impractical due to a significant increase in sampling requirements. This article introduces a novel motion correction technique that is capable of restoring image quality in motion corrupted two‐dimensional and three‐dimensional radial acquisitions without a priori assumptions about when motion occurs. The navigating properties of radial acquisitions—corroborated by multiple receiver coils—are exploited to detect actual instances of motion. Pseudorandom projection ordering provides flexibility of reconstructing navigator images from the obtained motion‐free variable‐width subsets for subsequent estimation of rigid body motion parameters by coregistration. The proposed approach does not require any additional navigators or external motion estimation schemes. The capabilities and limitations of the method are described and demonstrated through simulations and representative volunteer cranial acquisitions. Magn Reson Med 69:1094–1103, 2013. © 2012 Wiley Periodicals, Inc.