Chen C K, Chiueh T D, Chen J H
Department of Electrical Engineering, National Taiwan University, Taipei.
IEEE Trans Biomed Eng. 1999 Feb;46(2):186-91. doi: 10.1109/10.740881.
In this paper, we introduce a new neural-network architecture for reducing the acoustic noise level in magnetic resonance (MR) imaging processes. The proposed neural network (NN) consists of two cascaded time-delay NN's (TDNN's). This NN is used as the predictor of a feedback active noise control (ANC) system for reducing acoustic noises. Experimental results with real MR noises show that the proposed system achieved an average noise power attenuation of 18.75 dB, which compares favorably with previous studies. Preliminary results also show that with the proposed ANC system installed, acoustic MR noises are greatly attenuated while verbal communication during MRI sessions is not affected.
在本文中，我们介绍了一种用于降低磁共振（MR）成像过程中声学噪声水平的新型神经网络架构。所提出的神经网络（NN）由两个级联的时延神经网络（TDNN）组成。该神经网络用作反馈有源噪声控制（ANC）系统的预测器，以降低声学噪声。对实际MR噪声的实验结果表明，所提出的系统实现了18.75 dB的平均噪声功率衰减，与先前的研究相比具有优势。初步结果还表明，安装所提出的ANC系统后，MR声学噪声得到了极大的衰减，同时MRI检查期间的言语交流不受影响。
