基于稀疏表示的帕金森功能连接模式定位（英文）

发布时间：2018-02-26 16:35

本文关键词： 模式定位稀疏表示多变量模式分析功能连接　出处：《控制理论与应用》2017年06期 　论文类型：期刊论文

【摘要】：在脑成像数据分析中,基于稀疏表示的模式定位算法在群组水平分析中具有非常优秀的性能,但在单个数据集的情况下结果还不尽如人意.为此,文中在先前研究的基础上提出了一种改进算法,通过基于原始数据集生成多个派生数据集的方法,来改善算法在单个数据集分析中的不足.仿真结果表明改进后算法在性能上有显著的提高.文章随后将该改进算法应用于帕金森病异常功能连接模式定位分析之中,得到广泛分布于全脑的与该疾病相关的269个异常功能连接,由此对算法的有效性进行了验证,并可能有助于加强对与该疾病相关的病理生理机制的了解.
[Abstract]:In the analysis of brain imaging data, the pattern location algorithm based on sparse representation has excellent performance in group level analysis, but the result is not satisfactory in the case of a single data set. Based on the previous research, an improved algorithm is proposed to generate multiple derived datasets based on the original data set. The simulation results show that the performance of the improved algorithm is significantly improved. Then, the improved algorithm is applied to the localization analysis of abnormal functional connection mode for Parkinson's disease. A total of 269 abnormal functional connections related to the disease were obtained, which proved the effectiveness of the algorithm and may contribute to better understanding of the pathophysiological mechanisms associated with the disease.
【作者单位】：华南理工大学自动化科学与工程学院;
【基金】：Supported by National Natural Science Foundation of China(91120305) Guangdong Natural Science Foundation(2014A030312005)
【分类号】：R742.5;TP391.41

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