A Structure Design Method for Reduction of MRI Acoustic Noise

The acoustic problem of the split gradient coil is one challenge in a Magnetic Resonance Imaging and Linear Accelerator (MRI-LINAC) system. In this paper, we aimed to develop a scheme to reduce the acoustic noise of the split gradient coil. First, a split gradient assembly with an asymmetric configuration was designed to avoid vibration in same resonant modes for the two assembly cylinders. Next, the outer ends of the split main magnet were constructed using horn structures, which can distribute the acoustic field away from patient region. Finally, a finite element method (FEM) was used to quantitatively evaluate the effectiveness of the above acoustic noise reduction scheme. Simulation results found that the noise could be maximally reduced by 6.9 dB and 5.6 dB inside and outside the central gap of the split MRI system, respectively, by increasing the length of one gradient assembly cylinder by 20 cm. The optimized horn length was observed to be 55 cm, which could reduce noise by up to 7.4 dB and 5.4 dB inside and outside the central gap, respectively. The proposed design could effectively reduce the acoustic noise without any influence on the application of other noise reduction methods

Speech perception in MRI scanner noise by persons with aphasia

Purpose. To examine reductions in performance on auditory tasks by aphasic and neurologically-intact individuals as a result of concomitant MRI scanner noise. Methods. Four tasks together forming a continuum of linguistic complexity were developed. They included complex-tone pitch discrimination, same/different discrimination of minimal pair syllables, lexical decision, and sentence plausibility. Each task was performed by persons with aphasia (PWA) and by controls. The stimuli were presented in silence and also in the noise recorded from within the bore of a 3T MRI scanner at three signal-to-noise ratios (S/Ns). Results. Across the four tasks, the PWA scored lower than the controls and performance fell as a function of decreased S/N. However, the rate at which performance fell was not different across the two listener groups in any task. Conclusions. Depending upon the relative levels of the signals and noise, the intense noise accompanying MRI scanning has the potential to severely disrupt performance. However, PWA are no more susceptible to the disruptive influence of this noise than are unimpaired individuals usually employed as controls. Thus, fMRI data from aphasic and control individuals may be interpreted without complications associated with large interactions between scanner noise and performance reduction

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

Acoustic analysis of an induction motor with viscoelastic bearing supports

The demand for silent bearing applications has resulted in the development of an effective damping layer between the outer ring of a rolling bearing and the surrounding structure. By means of numerical modeling using both FEM and BEM techniques an induction motor for household appliances is analyzed. A hybrid modeling approach combining measured structural velocities with a BEM formulation is used to validate the acoustic model. The numerical results are compared with results obtained from sound intensity measurements estimating the radiated sound power level for a running electric mo tor. It is found that a relatively simple boundary element model is capable of predicting the radiated sound power in a wide frequency range. By using BEM in combination with the radiation modes formulation it is found that a properly designed viscoelastic layer in the vicinity of the bearing is theoretically capable of reducing a fair amount of sound emitted by the motor

Acoustic, psychophysical, and neuroimaging measurements of the effectiveness of active cancellation during auditory functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is one of the principal neuroimaging techniques for studying human audition, but it generates an intense background sound which hinders listening performance and confounds measures of the auditory response. This paper reports the perceptual effects of an active noise control (ANC) system that operates in the electromagnetically hostile and physically compact neuroimaging environment to provide significant noise reduction, without interfering with image quality. Cancellation was first evaluated at 600 Hz, corresponding to the dominant peak in the power spectrum of the background sound and at which cancellation is maximally effective. Microphone measurements at the ear demonstrated 35 dB of acoustic attenuation [from 93 to 58 dB sound pressure level (SPL)], while masked detection thresholds improved by 20 dB (from 74 to 54 dB SPL). Considerable perceptual benefits were also obtained across other frequencies, including those corresponding to dips in the spectrum of the background sound. Cancellation also improved the statistical detection of sound-related cortical activation, especially for sounds presented at low intensities. These results confirm that ANC offers substantial benefits for fMRI research