基于rsfMRI的海马子区分割及功能分析
首发时间:2016-06-21
摘要:背景:海马是记忆功能的核心脑区,海马子脑区的深入研究对认知相关精神疾病防治有着重要意义,本文通过谱聚类依据海马脑区静息态功能连接特征对海马区域进行分割,并探讨各区域功能连接特性。方法:在计算海马体素的功能连接矩阵的基础上使用谱聚类方法对连接矩阵进行聚类分析,从而实现对海马脑区的分割,最后通过种子点相关法对海马各子区域进行功能连接分析,探讨各子区域功能特征。结果:海马基于静息态功能连接特征进行谱聚类分割的结果与现有研究取得很好的一致性,且分割得到的海马各子区域具有各自的功能特性。
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Segmentation of the Hippocampus Based on the Resting Functional Connectivity and Functional Analysis of the Subregions
Abstract:Background: the hippocampus is a key brain region of memory system and the research of the subregions of it has an important significance on prevention and treatment of cognitive mental diseases. The research segmented the hippocampus according to resting-state functional connectivity feature by spectral clustering method and the segmentation based on the method proposed in this paper was consistent with clinical anatomy of the hippocampus. then the functional characteristics of the subregions were further studied. Methods: To realize the segmentation of the hippocampus, the thesis segmented functional connectivity matrix among the voxels of hippocampus by through spectral clustering. Finally, seed points correlation analysis was used to study the resting-state functional connectivity of subregions the hippocampus. Results: The segmentation based on the method proposed in this paper was consistent with clinical anatomy of the hippocampus and the function of the subregions of the hippocampus showed significant specificity.
Keywords: magnetic Resonance Imaging brain segmentation functional connectivity
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