MR影像体素形态学的阿尔茨海默病自动分类方法

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为了确定轻度认知功能障碍(MCI)与阿尔茨海默病(AD)患者发生萎缩的重要脑区,实现正常老年人(NC)对照组、MCI与AD三组人群的分类,选择了178名被试的脑部MR影像,利用体素形态学与方差分析方法,考察NC,MCI与AD三组人群的MR影像中灰质体积差异;然后,采用递归特征消去法对特征进行降维;最后,利用线性支持向量机对这3种人群进行分类.实验结果表明,MCI组与NC组、MCI组与AD组、AD组与NC组的平均分类准确率分别为(90.2±1.3)%,(74.7±0.9)%,100%.对分类产生重要影响的脑区包括海马、海马旁回、杏仁核、梭状回和嗅皮层等.所提方法不仅能有效揭示NC,MCI,AD三组人群的脑灰质差异,阐明MCI患者与AD患者脑区发生萎缩的过程与特性,而且能准确区分这3组人群,具有显著的临床应用价值.
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