基于BP神经网络的脑磁图偶极子源定位
Dipole source localization of MEG by BP neural networks.
作者信息
Kinouchi Y, Ohara G, Nagashino H, Soga T, Shichijo F, Matsumoto K
机构信息
Department of Electrical and Electronic Engineering, University of Tokushima, Japan.
出版信息
Brain Topogr. 1996 Spring;8(3):317-21. doi: 10.1007/BF01184791.
The purpose of this study was to examine the usefulness of BP neural network for source localization of MEG. Since the performance of this method does not depend on the complexity of brain parameters and source models, a homogeneous brain model and a single current dipole source are assumed for convenience. Localization accuracy was examined in relation to the configuration and scale of the network. As a result, average error for position and moment estimations was within 2% while the maximum error was about 5%. It was therefore concluded that the neural network method, was useful for MEG source localization, though some improvements are still necessary.
本研究的目的是检验BP神经网络用于脑磁图（MEG）源定位的有效性。由于该方法的性能不依赖于脑参数和源模型的复杂性，为方便起见，假设采用均匀脑模型和单个电流偶极子源。针对网络的配置和规模对定位精度进行了检验。结果表明，位置和矩估计的平均误差在2%以内，而最大误差约为5%。因此得出结论，神经网络方法对MEG源定位是有用的，尽管仍有必要进行一些改进。
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