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Active Control of Acoustic Noise by Magnetic Resonance Imaging: A Simulation Study

机译:磁共振成像对声噪声的主动控制:仿真研究

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In medical imaging for clinical diagnosis and biomedical research magnetic resonance imaging (MRI) is one of the prevailing techniques. A lot of subjects of MRI are annoyed by the loud noise that MRI generates. In the present study computer simulation of active control of the noise induced by MRI was performed. The sound generated by the measurement sequences for the brain was recorded with an IC recorder in an MRI scanner room. Prediction of the time series of the sound was attempted using linear prediction and artificial neural networks (ANN). By subtraction of the predicted value from the sound value the sound intensity is reduced. With several optimization techniques of ANN such as steepest decent method, Levenberg-Marquadt method, etc, active control of the noise was examined. In the present paper, the comparison of the simulation results of the prediction with those methods is described.
机译:在用于临床诊断和生物医学研究的医学成像中,磁共振成像(MRI)是流行的技术之一。 MRI产生的巨大噪音使很多MRI受试者烦恼。在本研究中,对由MRI诱发的噪声进行主动控制的计算机模拟得以执行。由大脑的测量序列产生的声音在MRI扫描室中用IC记录器记录。尝试使用线性预测和人工神经网络(ANN)来预测声音的时间序列。通过从声音值中减去预测值,可以降低声音强度。利用几种最先进的人工神经网络优化技术,例如最陡的体面方法,Levenberg-Marquadt方法等,研究了噪声的主动控制。在本文中,描述了预测的仿真结果与那些方法的比较。

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