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Research Papers

Mapping and Spectral Analysis of Acoustic Vibration in the Scanning Area of the Weak Field Magnetic Resonance Imager

[+] Author and Article Information
Jiří Přibil

Institute of Measurement Science,
Slovak Academy of Sciences,
Dúbravská cesta 9,
Bratislava SK-841 04, Slovakia
e-mail: jiri.pribil@savba.sk

Anna Přibilová

Institute of Electronics and Photonics,
Faculty of Electrical Engineering
and Information Technology,
SUT, Ilkovičova 3,
Bratislava SK-812 19, Slovakia

Ivan Frollo

Institute of Measurement Science,
Slovak Academy of Sciences,
Dúbravská cesta 9,
Bratislava SK-841 04, Slovakia

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received September 30, 2013; final manuscript received May 16, 2014; published online July 25, 2014. Assoc. Editor: Thomas J. Royston.

J. Vib. Acoust 136(5), 051005 (Jul 25, 2014) (10 pages) Paper No: VIB-13-1336; doi: 10.1115/1.4027791 History: Received September 30, 2013; Revised May 16, 2014

The paper describes measurement and calculation of 2D distribution of the vibration signal originated by the gradient coil system of the magnetic resonance imaging (MRI) equipment. The measurement experiments were performed at the bottom plastic holder of the scanning area of the open-air weak magnetic field MRI device. Selection of a usable type of a vibration sensor for measurement in a magnetic field with low B0 up to 0.2 T is also discussed. Realized calibration of the chosen sensor (sensitivity and frequency response) together with determination of the propagation time delay between the excitation impulses and the subsequently generated vibration signal is mentioned, too. The picked-up vibration signal exhibits harmonic character so it is suitable to describe it by determined spectral properties and features. Obtained statistical results of spectral analysis will be used to improve image sharpening and reduction of the motion effect in the MR pictures of thin layer samples and phantoms scanned by this MRI system.

Copyright © 2014 by ASME
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References

van den Brink, J. S., Watanabe, Y., Kuhl, C. K., Chung, T., Muthupillai, R., van Cauteren, M., Yamada, K., Dymarkowski, S., Bogaert, J., Maki, J. H., Matos, C., Casselman, J. W., and Hoogeveen, R. M., 2003, “Implications of SENSE MR in Routine Clinical Practice,” Eur. J. Radiol., 46(1), pp. 3–27. [CrossRef] [PubMed]
Bertram, H. C., Rasmussen, M., Busk, H., Oksbjerg, N., Karlsson, A. H., and Andersen, H. J., 2002, “Changes in Porcine Muscle Water Characteristics During Growth—An In Vitro Low-Field NMR Relaxation Study,” J. Magn. Reson., 157(2), pp. 267–276. [CrossRef] [PubMed]
Thybo, A. K., Andersen, H. J., Karlsson, A. H., Dønstrup, S., and Stødkilde-Jørgensen, H., 2003, “Low-Field NMR Relaxation and NMR-Imaging as Tools in Differentiation Between Potato Sample and Determination of Dry Matter Content in Potatoes,” LWT—Food Sci. Technol., 36(3), pp. 315–322. [CrossRef]
du Trémolet de Lacheisserie, É., Gignoux, D., and Schlenker, M., 2005, Magnetism: Fundamentals, Springer Science + Business Media, Berlin.
Moelker, A., Wielopolski, P. A., and Pattynama, M. T., 2003, “Relationship Between Magnetic Field Strength and Magnetic-Resonance-Related Acoustic Noise Levels,” Mag. Reson. Mater. Phys., Biol. Med., 16(1), pp. 52–55. [CrossRef]
Frollo, I., Andris, P., Přibil, J., and Juráš, V., 2007, “Indirect Susceptibility Mapping of Thin-Layer Samples Using Nuclear Magnetic Resonance Imaging,” IEEE Trans. Magn., 43(8), pp. 3363–3367. [CrossRef]
Oveisi, A., Gudarzi, M., Mohammadi, M. M., and Doosthoseini, A., 2013, “Modeling, Identification and Active Vibration Control of a Funnel-Shaped Structure Used in MRI Throat,” J. Vibroeng., 15(1), pp. 438–449, available at: http://jve.lt/Vibro/JVE-2013-15-1/JVE-2013-15-1-961.pdf
Rudd, B. W., Lee, J. H., Lim, T. C., and Li, M., 2012, “In Situ Active Noise Cancellation Applied to Magnetic Resonance Imaging,” ASME J. Vib. Acoust., 134(1), p. 011017. [CrossRef]
Baker, M. A., 2013, “Reduction of MRI Acoustic Noise Achieved by Manipulation of Scan Parameters—A Study Using Veterinary MR Sequences,” Radiography, 19(1), pp. 11–16. [CrossRef]
E-scan Opera, 2008, Image Quality and Sequences Manual, 830023522 Rev. A, Esaote, Genova, Italy.
Kwak, M. K., and Yang, D. H., 2013, “Active Vibration Control of a Ring-Stiffened Cylindrical Shell in Contact With Unbounded External Fluid and Subjected to Harmonic Disturbance by Piezoelectric Sensor and Actuator,” J. Sound Vib., 332(20), pp. 4775–4797. [CrossRef]
Žiaran, S., and Darula, R., 2013, “Determination of the State of Wear of High Contact Ratio Gear Sets by Means of Spectrum and Cepstrum Analysis,” ASME J. Vib. Acoust., 135(2), pp. 1–10. [CrossRef]
Fraden, J., 2010, Handbook of Modern Sensors. Physics, Designs, and Applications, 4th ed., Springer, New York.
Niedżwiecki, M., and Meller, M., 2013, “Generalized Adaptive Comb Filters/Smoothers and Their Application to the Identification of Quasi-Periodically Varying Systems and Signals,” Automatica, 49(6), pp. 1601–1613. [CrossRef]
Sierra, C. V. R., Versluis, M. J., Hoogduin, J. M., and Duifhuis, H. D., 2008, “Acoustic fMRI Noise: Linear Time-Invariant System Model,” IEEE Trans. Biomed. Eng., 55(9), pp. 2115–2123. [CrossRef] [PubMed]
Borza, D. N., 2011, “Vibration Measurement by Speckle Interferometry Between High Spatial and High Temporal Resolution,” Holography, Research, and Technologies, J.Rosen, ed., InTech, Rjeka, Croatia, pp. 325–346.
Phidgets 1104, 2009, Vibration Sensor Product Manual, Phidgets, Inc., Calgary, Canada.
Raitio, T., Suni, A., Vainio, M., and Alku, P., 2013, “Synthesis and Perception of Breathy, Normal, and Lombard Speech in the Presence of Noise,” Comput. Speech Lang., 28(2), pp. 648–664. [CrossRef]
Misra, H., Ikbal, S., Sivadas, S., and Bourlard, H., 2005, “Multi-Resolution Spectral Entropy Feature for Robust ASR,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’05), Philadelphia, PA, March 18–23, pp. 253–256. [CrossRef]
Le, P. N., Ambikairajah, E., Epps, J., Sethu, V., and Choi, E. H. C., 2011, “Investigation of Spectral Centroid Features for Cognitive Load Classification,” Speech Commun., 53(4), pp. 540–551. [CrossRef]
Madhu, N., 2009, “Note on Measures for Spectral Flatness,” Electron. Lett., 45(23), pp. 1195–1196. [CrossRef]
Sinha, J. K., 2005, “On Standardisation of Calibration Procedure for Accelerometer,” J. Sound Vib., 286(1–2), pp. 417–427. [CrossRef]
Frollo, I., Andris, P., Přibil, J., Dermek, T., and Gogola, D., 2013, “Soft Magnetic Material Testing Using Magnetic Resonance Imaging,” Adv. Mater. Res., 740, pp. 618–623. [CrossRef]

Figures

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Fig. 1

Scanning space of MRI: (1)—RF knee coil with testing phantom, (2) and (3)—lower and upper permanent magnets and gradient coils

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Fig. 2

Arrangement of sensors on vibration exciter for calibration experiment: (1) and (2)—reference accelerometers KD35a, KD12, (3)—tested vibration sensor SB-1

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Fig. 3

Relative sensitivity of the sensors at fref = 125 Hz; UexcBa0 = 360 mV; Ba0 = {12.9 (SB-1), 4.99 (KD35a), 4.22 (KD12)} mV/ms−2

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Fig. 4

Frequency responses: acceleration sensitivity for SB-1, KD35a, KD12 (a), velocity sensitivity for SB-1 (b); fref = 125 Hz; U excBa0 = 360 mV

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Fig. 6

Arrangement of propagation time delay measurement: RF coil with water phantom (1), SB-1 sensor (2), and experimental coil for pick-up of electrical excitation pulses (3)

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Fig. 7

Distribution of the relative vibration level in (dB): at basic positions 0–18 in 15 × 9 grid with 2D contour map (upper), at extended positions 0–50 with 2D contour map (lower); sequence No. 1

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Fig. 8

Distribution of the relative vibration level in (dB) at positions 0–18 (upper), 2D contour maps (lower); sequences: No. 2. (a), No. 4 (b), and No. 8 (c)

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Fig. 9

Distribution of the excitation signal in (mV): at basic positions 0–18 in 15 × 9 grid with 2D contour map (upper), at extended positions 0–50 with 2D contour map (lower); sequence No. 1

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Fig. 10

Mean values of time delay between electric excitation and vibration signal: from positive part of signal (a), from negative part of signal (b) at positions P0, P1, and P4

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Fig. 11

Mean values of spectral features HNR (a), SFM (b), SC (c), and SE (d) at positions P0, P1, and P4

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Fig. 12

Basic statistical properties of spectral features: HNR (a), SFM (b), SC (c), and SE (d) at position P0

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Fig. 13

Typical waveforms of excitation signals for sequences Nos. 1–8 ((a)–(h)) at position P0, fs = 16 kHz

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Fig. 14

Typical waveforms of vibration signals for sequences Nos. 1–8 ((a)–(h)) at position P0, fs = 16 kHz

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Fig. 15

Spectrograms of vibration signals for sequences Nos. 1–8 ((a)–(h)) at position P0, fs = 16 kHz

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Fig. 16

Periodograms and spectral envelopes of vibration signals for sequences Nos. 1–8 ((a)–(h)) at position P0, fs = 16 kHz

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