面向脑皮层厚度的特征选择方法研究
针对当前阿尔茨海默症脑皮层厚度数据的特征选择算法分类精度问题,提出一种融合的特征选择算法。分析处理轻度认知障碍人群和正常老年人的脑皮层厚度的核磁共振图像数据,基于此数据融合最小冗余和最大相关方法与Relief方法,并使用粒子群优化算法求得最优权重;使用此权重融合两种方法对脑皮层厚度的脑区特征进行特征选择,选出使分类准确率较高的特征。实验使用留一验证对实验结果进行评估,选出的特征对轻度认知障碍人群与正常老年人的分类效果好于当前流行的特征选择方法。...
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| Published in | 计算机应用研究 Vol. 34; no. 3; pp. 675 - 677 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
山东师范大学信息科学与工程学院,济南,250014%兰州大学信息科学与工程学院,兰州,730000
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2017.03.008 |
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| Summary: | 针对当前阿尔茨海默症脑皮层厚度数据的特征选择算法分类精度问题,提出一种融合的特征选择算法。分析处理轻度认知障碍人群和正常老年人的脑皮层厚度的核磁共振图像数据,基于此数据融合最小冗余和最大相关方法与Relief方法,并使用粒子群优化算法求得最优权重;使用此权重融合两种方法对脑皮层厚度的脑区特征进行特征选择,选出使分类准确率较高的特征。实验使用留一验证对实验结果进行评估,选出的特征对轻度认知障碍人群与正常老年人的分类效果好于当前流行的特征选择方法。 |
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| Bibliography: | Sun Fujun1 , Hu Bin2, Zheng Weihao2, Yao Zhijun2 （1. College of Information Science ＆ Engineering; Shandong Normal University, Jinan 250014, China; 2. School of Information Science ＆ En gineering, Lanzhou University, Lanzhou 730000, China） 51-1196/TP This paper proposed a hybrid feature selection algorithm,in view of the current problems of the classification accuracy of feature selection algorithm for cortical thickness data of Blzheimer＇s disease. Firstly,this paper analyzed and processed magnetic resonance image cortical thickness＇ data of mild cognitive impairment and normal elderly population. Based on this data it fused minimum redundancy and maximum correlation method and Relief method,and used particle swarm optimization algorithm to obtain the optimal weights. Then,it did feature selection using this weight fusion of two kinds of methods of cortical thickness for features of brain regions,selected characteristics that made the higher classification accuracy. The experiment uses leave-one-out cross vali |
| ISSN: | 1001-3695 |
| DOI: | 10.3969/j.issn.1001-3695.2017.03.008 |