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Intrinsic detection of motion in segmented sequences
Author(s) -
Mendes Jason,
Parker Dennis L.
Publication year - 2011
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.22681
Subject(s) - motion (physics) , artificial intelligence , computer vision , computer science , translation (biology) , function (biology) , plane (geometry) , object (grammar) , dispersion (optics) , algorithm , mathematics , pattern recognition (psychology) , physics , geometry , optics , biology , biochemistry , chemistry , evolutionary biology , messenger rna , gene
While many motion correction techniques for MRI have been proposed, their use is often limited by increased patient preparation, decreased patient comfort, additional scan time, or the use of specialized sequences not available on many commercial scanners. For this reason, we propose a simple self‐navigating technique designed to detect motion in segmented sequences. We demonstrate that comparing two segments containing adjacent sets of k ‐space lines results in an aliased error function. A global shift of the aliased error function indicates the presence of in‐plane rigid‐body translation, while other types of motion are evident in the dispersion or breadth of the error function. Since segmented sequences commonly acquire data in sets of adjacent k ‐space lines, this method provides these sequences with an inherent method of detecting object motion. Motion corrupted data can then be reacquired proactively or in some cases corrected or removed retrospectively. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.