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k ‐Space weighted least‐squares algorithm for accurate and fast motion extraction from magnetic resonance navigator echoes
Author(s) -
Nguyen Thanh D.,
Wang Yi,
Watts Richard,
Mitchell Ian
Publication year - 2001
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.1294
Subject(s) - algorithm , displacement (psychology) , noise (video) , motion (physics) , k space , phase (matter) , computer science , space (punctuation) , least squares function approximation , line (geometry) , artificial intelligence , mathematics , computer vision , physics , mathematical analysis , geometry , image (mathematics) , psychology , statistics , fourier transform , quantum mechanics , estimator , psychotherapist , operating system
Navigator echoes provide an effective method to monitor physiological motion, allowing motion artifacts to be suppressed by modifying the data acquisition accordingly. The displacement can be measured directly from the navigator phase using an algorithm suggested by Ahn and Cho (IEEE Trans Med Imaging 1987;MI‐6:32–36). Although computationally efficient, it is susceptible to noise, particularly contributions from points at the edges of k ‐space. A k ‐space weighted least‐squares (kLS) algorithm is proposed which fits a straight line to the motion‐induced phase shift. The linear fit is weighted strongly to high SNR points near the k ‐space center and only weakly to the poor SNR points at the edges of k ‐space. This algorithm was found to be as efficient as Ahn's algorithm but more robust against noise. Magn Reson Med 46:1037–1040, 2001. © 2001 Wiley‐Liss, Inc.