功能磁共振成像与脑电的融合及其应用

作为当今医学影像技术研究中的热点问题之一,多模态医学影像融合技术的研究及其研究成果,对认知科学的研究和临床治疗有着重要的意义.提出了一种基于独立分量分析(ICA)的fMRI受限等效偶极子模型(简称FC-ECD)来解决fMRI与EEG的融合问题.方法首先利用ICA,剔除原始信号中的噪声,提取有效ERP成分(同时可以对偶极子的数量进行估计);然后基于理想4层头模型,利用fMRI激活点的空间信息作为限制条件,对提取出的ERP成分进行精确的定位,从而减少了计算量并取得了很好的效果;然后,通过仿真实验的结果验证了方

Fusion of Functional Magnetic Resonance Imaging & Electroencephalograph and Its Application

Multi-Modality fusion is one of the hottest discussed issues in the current research of medical image processing and it has a deep impact on the cognitive science and clinical treatment. In this paper, an fMRI-constraint equivalent dipole model (FC-ECD) based on ICA is proposed to solve the fusion of fMRI and EEG. The ICA is adopted as a preprocessing step to exclude the noise and select the available ERP components. At the same time, it can provide a prior estimate of the number of dipoles. Then considering the spatial information provided by fMRI, the selected ERP components are localized by FC-ECD model based on an ideal four-sphere head model. Thus it can reduce the computation time dramatically. Finally, the simulation study proves the correctness and validity of the method proposed in the paper and the human study coincides with the physiology fact.