机构地区: 北京理工大学珠海学院
出 处: 《信息技术》 2013年第5期10-15,共6页
摘 要: 鉴于寻找抑郁症诊疗生物指标的迫切需求以及日益成熟的fMRI数据分析技术和模式分类技术,进行了静息态fMRI的功能连接分析方法研究及应用。利用fMRI采集28名健康被试和38名抑郁症患者静息态功能磁共振数据,采用模型驱动的分析方法,从时域(相关分析、偏相关分析)和频域(相干分析、互信息分析)两个角度进行分析,对抑郁症患者和健康对照者进行选定脑区之间的各种方法的功能连接分析,研究结果表明抑郁症患者在脑功能连接上与健康对照组的显著异常,通过这些异常的指标作为特征进行模式分类,对于建立抑郁症诊疗的影像学指标起到了一定作用,从而可以更好地辅助抑郁症临床诊断和疗效评判。 In view of the urgent need of looking for the biological indicators for the diagnosis and treatment of depression, as well as the growing maturity of fMRI data analysis and pattern classification techniques, this paper studies on the functional connectivity analysis and its application. It focuses on the various model-driven methods of resting state fMRI functional connectivity analysis using the fMRI collection of 28 healthy subjects and 38 patients with depression. It not only includes cross-correlation analysis and partial cross-correlation analysis in the time domain but also coherence analysis and mutual information analysis in the frequency domain. This demonstrates that the selection methods in the experiment are feasible and can distinguish the depression and the healthy. It places a certain role to establish the physiological indicator for the diagnosis and treatment of depression, thus it can better aid the clinical diagnosis and treatment.
关 键 词: 静息态功能磁共振成像 功能连接 模型驱动 时频域分析 分类 抑郁症
领 域: [自动化与计算机技术] [自动化与计算机技术]