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Evaluation of an independent linear model for acoustic noise on a conventional MRI scanner and implications for acoustic noise reduction
Author(s) -
Wu Ziyue,
Kim YoonChul,
Khoo Michael C.K.,
Nayak Krishna S.
Publication year - 2014
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.24798
Subject(s) - acoustics , microphone , superposition principle , noise reduction , sound pressure , waveform , noise (video) , physics , mathematics , computer science , mathematical analysis , image (mathematics) , quantum mechanics , voltage , artificial intelligence
Purpose To evaluate an independent linear model for gradient acoustic noise on a conventional MRI scanner, and to explore implications for acoustic noise reduction in routine imaging. Methods Acoustic noise generated from each physical gradient axis was modeled as the prescribed gradient waveform passed through a linear time‐invariant system. Homogeneity and superposition properties were experimentally determined. We also developed a new method to correct relative time shifts between the measured impulse responses for different physical gradient axes. Model accuracy was determined by comparing predicted and measured sound using normalized energy difference. Transfer functions were also measured in subjects with different body habitus and at multiple microphone locations. Results Both superposition and homogeneity held for each physical gradient axis with errors less than 3%. When all gradients were on simultaneous sound prediction, error was reduced from 32% to 4% after time‐shift correction. Transfer functions also showed high sensitivity to body habitus and microphone location. Conclusion The independent linear model predicts MRI acoustic noise with less than 4% error. Acoustic transfer functions are highly sensitive to body habitus and position within the bore, making it challenging to produce a general approach to acoustic noise reduction based on avoiding system resonance peaks. Magn Reson Med 71:1613–1620, 2014. © 2013 Wiley Periodicals, Inc .