Analysis of Influence of Coil Gradient System on Vibration Properties and Acoustic Noise Level Generated by the Low Field MRI Device

Open access


The paper focuses on investigation of influence of the volume inserted in the scanning area of the magnetic resonance imaging (MRI) device working with a low magnetic field generated by a pair of permanent magnets on vibration and acoustic noise. In addition, its aim is to evaluate the influence of different types of used scan sequences, different settings of slice orientation and scan parameters on the energy and spectral properties of vibration and noise generated by the gradient coil system of the MRI device. Two basic measurements were performed within this work: mapping of sound pressure levels in the MRI device vicinity and parallel acquisition of vibration signals by sensors mounted on the lower and upper parts of the MRI gradient system. The paper next analyzes changes in properties of the vibration signals for the examined person lying in the scanning area compared with the situation of using only the testing phantom. Spectral characteristics of the recorded vibration signals are then analyzed statistically, and compared visually and numerically. The obtained results of the detailed analysis will be used for improvement of noise suppression algorithms applied to a speech signal recorded simultaneously with scanning of the human vocal tract for its 3D modeling.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] Esaote S.p.A. (2008). E-scan Opera. Image Quality and Sequences Manual. 830023522 Rev. A.

  • [2] Wang F. Mechefske C.K. (2008). Vibration analysis and testing of a thin-walled gradient coil model. Journal of Sound and Vibration 311 554-566.

  • [3] Winkler S.A. Alejski A. Wade T. McKenzie C.A. Rutt B.K. (2017). On the accurate analysis of vibroacoustics in head insert gradient coils. Magnetic Resonance in Medicine 78 1635-1645.

  • [4] Latta P. Gruwel M.L.H. Edie E. Šramek M. Tomanek B. (2004). Single point imaging with suppressed sound pressure levels through gradientshape adjustment. Journal of Magnetic Resonance 170 177-183.

  • [5] Glowacz A. (2015). Recognition of acoustic signals of synchronous motors with the use of MoFS and selected classifiers. Measurement Science Review 15 (4) 167-175.

  • [6] Winkler S.A. Schmitt F. Landes H. de Bever J. Wade T. Alejski A. Rutt B.K. (2018). Gradient and shim technologies for ultra high field MRI. NeuroImage 168 59-70.

  • [7] Wang Y. Liu F. Li Y. Tang F. Crozier S. (2016). Asymmetric gradient coil design for use in a short open bore magnetic resonance imaging scanner. Journal of Magnetic Resonance 269 203-212.

  • [8] Weiger M. Overweg J. Rosler M.B. et al. (2018). A high-performance gradient insert for rapid and short-T2 imaging at full duty cycle. Magnetic Resonance in Medicine 79 3256-3266.

  • [9] Přibil J. Přibilova A. Frollo I. (2014). Mapping and spectral analysis of acoustic vibration in the scanning area of the weak field magnetic resonance imager. Journal of Vibration and Acoustics - Transactions of the ASME 136 (5) 051005.

  • [10] Přibil J. Přibilova A. Frollo I. (2016). Comparison of mechanical vibration and acoustic noise in the open-air MRI. Applied Acoustics 105 13-23.

  • [11] Luukinen J.M. Aalto D. Malinen J. et al. (2018). A novel marker based method to teeth alignment in MRI. Measurement Science Review 18 (2) 79-85.

  • [12] Diedrichsen J. Balsters J.H. Flavell J. Cussans E. Ramnani R. (2009). A probabilistic MR atlas of the human cerebellum. NeuroImage 46 (1) 39-46.

  • [13] Hamaguchi T. Miyati T. Matsushita T. Ohno N. (2014). Analysis of spatial dependence of acoustic noise transfer function in magnetic resonance imaging. In European Congress of Radiology (ECR 2014) March 6-10 2014 Vienna Austria.

  • [14] Liang Z.P. Lauterbur P.C. (1999). Principles of Magnetic Resonance Imaging: A Signal Processing Perspective. Wiley-IEEE Press.

  • [15] Fraden J. (2010). Handbook of Modern Sensors: Physics Designs and Applications. Springer.

  • [16] Mechefske C.K. (2008). Vibration in MRI scanners. In Biomedical Applications of Vibration and Acoustics in Therapy Bioeffect And Modeling. ASME 329-349.

  • [17] Přibil J. Horaček J. Horak P. (2011). Two methods of mechanical noise reduction of recorded speech during phonation in an MRI device. Measurement Science Review 11 (3) 92-98.

  • [18] Wei J. Liu J. Fang Q. Lu W. Dang J. Honda K. (2016). A novel method for constructing 3D geometric articulatory models. Journal of Signal Processing Systems 82 295-302.

  • [19] Dutilleux P. Zolzer U. (2002). Filters. In DAFX - Digital Audio Effects. John Wiley & Sons 31-62.

Journal information
Impact Factor

IMPACT FACTOR 2018: 1.122
5-year IMPACT FACTOR: 1.157

CiteScore 2018: 1.39

SCImago Journal Rank (SJR) 2018: 0.325
Source Normalized Impact per Paper (SNIP) 2018: 0.881

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 165 135 5
PDF Downloads 128 104 1