[1]黄嘉爽,梅雪,袁晓龙,等.脑功能网络的fMRI特征提取及脑部疾病机器识别[J].智能系统学报,2015,10(2):248-254.[doi:10.3969/j.issn.1673-4785.201312043]
HUANG Jiashuang,MEI Xue,YUAN Xiaolong,et al.FMRI feature extraction and identification of brain diseases based on the brain functional network[J].CAAI Transactions on Intelligent Systems,2015,10(2):248-254.[doi:10.3969/j.issn.1673-4785.201312043]
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HUANG Jiashuang,MEI Xue,YUAN Xiaolong,et al.FMRI feature extraction and identification of brain diseases based on the brain functional network[J].CAAI Transactions on Intelligent Systems,2015,10(2):248-254.[doi:10.3969/j.issn.1673-4785.201312043]
脑功能网络的fMRI特征提取及脑部疾病机器识别
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第2期
页码:
248-254
栏目:
学术论文—机器感知与模式识别
出版日期:
2015-04-25
- Title:
- FMRI feature extraction and identification of brain diseases based on the brain functional network
- Keywords:
- fMRI; schizophrenia; complex network theory; feature extraction; brain disease; machine recognition
- 分类号:
- TP391.4
- 文献标志码:
- A
- 摘要:
- 脑部疾病的机器识别是医学图像领域研究的热点。传统的功能磁共振图像研究方法大多只针对部分脑区。考虑到脑功能网络具有全局性的特征,利用静息态功能磁共振图像数据,在全脑范围内使用极大重叠离散小波变换,分别构建加权和无权脑功能网络,运用复杂网络理论对网络结构进行分析研究,提取网络聚集系数作为分类识别的特征分量。将该文方法用于对精神分裂症患者的识别,由识别率、灵敏度、特异度表明,该方法能够提高识别效果,且具有普遍适应性,能推广到其他脑部疾病的机器识别应用中。
- Abstract:
- The machine recognition of brain diseases is a hotspot issue in the field of medical images. However, traditional fMRI image analysis only treats part of the brain region. Considering the overall characteristics of the brain network, the maximal overlap discrete wavelet transform is used to construct weighted and binary networks based on the rest-fMRI data. The complex networks theory is applied to the network structure analysis. Finally, the clustering coefficient of the network is extracted as the characteristic component of classification identification, which allowed the separation of schizophrenia patients from normal control subjects. This method is applied to the recognition of schizophrenia in this paper. The experimental results of recognition rate, sensitivity and specificity show that this method is able to improve the effect of recognition and has the universal adaptability, which can be extended to the recognition of other brain diseases.
- 参考文献/References:
-
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备注/Memo
收稿日期:2013-12-24;改回日期:。
基金项目:国家自然科学基金资助项目(51205185).
作者简介:黄嘉爽,男,1988年生,硕士研究生,主要研究方向为模式识别、图像处理;梅雪,女,1975年生,副教授,主要研究方向为图像处理、模式识别及计算机视觉。
通讯作者:黄嘉爽.E-mail:hjshdym@163.com.
更新日期/Last Update:
2015-06-15