| 引用本文: | 雷震,胡德文,周宗谭,等.一种基于统计参数映射融合独立成分分析的新的激活区探测方法.[J].国防科技大学学报,2003,25(3):96-99.[点击复制] |
| LEI Zhen,HU Dewen,ZHOU Zongtan,et al.A New Activation Detecting Method Based on Combination of Statistical Parametric Mapping with the Independent Component Analysis[J].Journal of National University of Defense Technology,2003,25(3):96-99[点击复制] |
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| 一种基于统计参数映射融合独立成分分析的新的激活区探测方法 |
| 雷震1, 胡德文2, 周宗谭2, 朱文珍3 |
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(1.国防科技大学 人文与管理学院，湖南 长沙 410073;2.国防科技大学 机电工程与自动化学院，湖南 长沙 410073;3.华中科技大学 同济医学院同济医院放射科，湖北 武汉 430032)
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| 摘要: |
| 统计参数映射在某种程度上依赖于广义线性模型和高斯场理论。广义线性模型的缺陷在于这些假设不能很好地表示fMRI数据，并且脑活动分布模式和血液动力学模型也不能由广义线性模型回归方程来恰如其分地模拟。而独立成分分析不能够提供每一独立成分激活区的显著性估计，这使得实验者不能够很好地解释所获得的结果。提出一种将SPM和ICA技术进行融合的方法，此方法可以将ICA自身的某些优势和GLM的假设检验方法结合起来，互相取长补短。实验结果证明了这种方法在探测由运动任务所产生的激活区方面是有效的。 |
| 关键词: 统计参数映射 独立成分分析 功能磁共振成像 广义线性模型 |
| DOI： |
| 投稿日期：2002-12-23 |
| 基金项目:国家973预研专项基金 |
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| A New Activation Detecting Method Based on Combination of Statistical Parametric Mapping with the Independent Component Analysis |
| LEI Zhen1, HU Dewen2, ZHOU Zongtan2, ZHU Wenzhen3 |
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(1.College of Humanities and Management, National Univ. of Defense Technology, Changsha 410073,China;2.College of Mechatronics Engineering and Automation, National Univ. of Defense Technology,Changsha 410073,China;3.Department of Radiology,Tong Ji Hospital, Tong Ji Medical School, Huazhong Univ. of Sci. & Tech., Wuhan 430032,China)
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| Abstract: |
| Statistical parametric mapping (SPM) depends on the general linear model(GLM) and the theory of Gaussian fields to some extent. But the disadvantages of the GLM are related to the fact that these assumptions outlined do not fairly represent the fMRI data. Also, hemodynamics and distributed patterns of the brain activity may not be well modeled by the GLM regression framework. While, the independent component analysis(ICA) does not provide the investigator with a significance estimate for each component activation, which may discourage experimenters from attempting to interpret the results. The paper proposes a method which combines some of thebenefits of ICA with the hypothesis-testing approach of the SPM. Experimental results demonstrate that the proposed method is effective for detecting the activations resulting from a motor task. |
| Keywords: statistical parametric mapping independent component analysis fMRI, general linear model |
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