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| 一种基于独立成分分析的功能磁共振数据处理方法 | |
| 引用本文： | 陈华富,尧德中,周可,周天罡,卓彦,陈霖.一种基于独立成分分析的功能磁共振数据处理方法[J].生物医学工程学杂志,2002,19(1):64-66. |
| 作者姓名： | 陈华富 尧德中 周可 周天罡 卓彦 陈霖 |
| 作者单位： | 1. 电子科技大学,应用数学系,成都,610054;电子科技大学,生物医学信息检测与智能信息处理重点实验室,成都,610054 2. 电子科技大学,生物医学信息检测与智能信息处理重点实验室,成都,610054;中国科技大学,北京认知科学开放实验室,北京,100039 3. 中国科技大学,北京认知科学开放实验室,北京,100039 |
| 基金项目： | 国家自然科学重大基金资助项目 ( 6 9790 0 80 )，973项目 ( G19980 30 5 0 3) |
| 摘 要： | 独立成分分析（ICA）是统计信号处理中的一项新技术，用来从混合信号的多维观测中提取具有统计独立性的成分。我们针对功能磁共振数据处理，采用先对相邻的两体元信号作ICA分离，然后与参考信号进行相关，把相关系数大于一定阈值的体元作为刺激引起兴奋的体元，从而实现刺激的功能定位。经实际脑功能磁共振数据试验，初步证明了方法的有效性。 |
| 关 键 词： | 独立成分分析 功能磁共振成像 视觉刺激 |
A Method Based on Independent Component Analysis for Processing fMRI Data |
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| Chen Huafu , Yao Dezhong , Zhou Ke Zhou Tiangang Zhuo Yan Chen Lin.A Method Based on Independent Component Analysis for Processing fMRI Data[J].Journal of Biomedical Engineering,2002,19(1):64-66. | |
| Authors: | Chen Huafu Yao Dezhong Zhou Ke Zhou Tiangang Zhuo Yan Chen Lin |
| Affiliation: | Dept of Applied Math, University of Electronic Science and Technology of China, Chengdu 610054. |
| Abstract: | Independent component analysis (ICA) is a new technique in statistical signal processing to extract independent components from multidimensional measurements of mixed signals. In this paper, for the processing of functional magnetic resonance imaging(fMRI) data, two signals of near voxels are used as the mixed signals and are separated by ICA. The correlation coefficients between the reference signal and the separated signals are calculated and those voxels whose correlation coefficients are greater than a threshold are considered to be the activated voxels by the stimulation, and so the functional localization of the stimulation is completed. The validity of the method was primarily proved by trial of real brain functional magnetic resonance imaging data. |
| Keywords: | Independent component analysis Functional magnetic resonance imaging Visual stimulation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
