Simulation study on active noise control for a 4-T MRI scanner.

The purpose of this work is to study computationally the possibility of the application of a hybrid active noise control technique for magnetic resonance imaging (MRI) acoustic noise reduction. A hybrid control system combined with both feedforward and feedback loops embedded is proposed for potential application on active MRI noise reduction. A set of computational simulation studies were performed. Sets of MRI acoustic noise emissions measured at the patient's left ear location were recorded and used in the simulation study. By comparing three different control systems, namely, the feedback, the feedforward and the hybrid control, our results revealed that the hybrid control system is the most effective. The hybrid control system achieved approximately a 20-dB reduction at the principal frequency component. We concluded that the proposed hybrid active control scheme could have a potential application for MRI scanner noise reduction.

[1]  M. Quirk,et al.  Anxiety in patients undergoing MR imaging. , 1989, Radiology.

[2]  Teik C. Lim,et al.  Modeling active vibration control of a geared rotor system , 2004 .

[3]  Stephen J. Elliott,et al.  Signal Processing for Active Control , 2000 .

[4]  Dennis Norris,et al.  Automated post‐hoc noise cancellation tool for audio recordings acquired in an MRI scanner , 2005, Human brain mapping.

[5]  A R Palmer,et al.  Sound‐Level Measurements and Calculations of Safe Noise Dosage During EPI at 3 T , 2000, Journal of magnetic resonance imaging : JMRI.

[6]  F G Shellock,et al.  Auditory noise associated with MR procedures: a review. , 2000, Journal of magnetic resonance imaging : JMRI.

[7]  A. Goldman,et al.  Reduction of sound levels with antinoise in MR imaging. , 1989, Radiology.

[8]  Xiangcheng Chu,et al.  Characteristic analysis of an ultrasonic micromotor using a 3 mm diameter piezoelectric rod , 2004 .

[9]  A R Palmer,et al.  Active control of the volume acquisition noise in functional magnetic resonance imaging: method and psychoacoustical evaluation. , 2001, The Journal of the Acoustical Society of America.

[10]  R. Gangarosa,et al.  Operational safety issues in MRI. , 1987, Magnetic resonance imaging.

[11]  R E Brummett,et al.  Potential hearing loss resulting from MR imaging. , 1988, Radiology.

[12]  M McJury,et al.  The use of active noise control (ANC) to reduce acoustic noise generated during MRI scanning: some initial results. , 1997, Magnetic resonance imaging.

[13]  Adriaan Moelker,et al.  Importance of bone‐conducted sound transmission on patient hearing in the MR scanner , 2005, Journal of magnetic resonance imaging : JMRI.

[14]  J. Melcher,et al.  Isolating the auditory system from acoustic noise during functional magnetic resonance imaging: examination of noise conduction through the ear canal, head, and body. , 2001, The Journal of the Acoustical Society of America.

[15]  Sen M. Kuo,et al.  Active Noise Control Systems: Algorithms and DSP Implementations , 1996 .

[16]  Gene F. Franklin,et al.  Feedback Control of Dynamic Systems , 1986 .

[17]  Jing-Huei Lee,et al.  Acoustic noise characteristics of a 4 Telsa MRI scanner , 2006, Journal of magnetic resonance imaging : JMRI.

[18]  Tzi-Dar Chiueh,et al.  Active cancellation system of acoustic noise in MR imaging , 1999, IEEE Transactions on Biomedical Engineering.

[19]  P. Jezzard,et al.  Sources of distortion in functional MRI data , 1999, Human brain mapping.

[20]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[21]  Bruce A. Francis,et al.  Feedback Control Theory , 1992 .

[22]  E Borg,et al.  Magnetic resonance imaging of the cochlea, spiral ganglia and eighth nerve of the guinea pig. , 1999, Neuroreport.