Depression Disorder Classification of fMRI Data Using Sparse Low-Rank Functional Brain Network and Graph-Based Features
Wang, Xin1; Ren, Yanshuang2; Zhang, Wensheng1; Zhang Wensheng
2017
发表期刊COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
卷号2017期号:2017页码:1
文章类型Article
摘要Study of functional brain network (FBN) based on functional magnetic resonance imaging (fMRI) has proved successful in depression disorder classification. One popular approach to construct FBN is Pearson correlation. However, it only captures pairwise relationship between brain regions, while it ignores the influence of other brain regions. Another common issue existing in many depression disorder classification methods is applying only single local feature extracted from constructed FBN. To address these issues, we develop a new method to classify fMRI data of patients with depression and healthy controls. First, we construct the FBN using a sparse low-rank model, which considers the relationship between two brain regions given all the other brain regions. Moreover, it can automatically remove weak relationship and retain the modular structure of FBN. Secondly, FBN are effectively measured by eight graph-based features from different aspects. Tested on fMRI data of 31 patients with depression and 29 healthy controls, our method achieves 95% accuracy, 96.77% sensitivity, and 93.10% specificity, which outperforms the Pearson correlation FBN and sparse FBN. In addition, the combination of graph-based features in our method further improves classification performance. Moreover, we explore the discriminative brain regions that contribute to depression disorder classification, which can help understand the pathogenesis of depression disorder.
关键词Depression Classification Fmri Sparse Low-rank
WOS标题词Science & Technology ; Life Sciences & Biomedicine
DOI10.1155/2017/3609821
关键词[WOS]RESTING-STATE FMRI ; MAJOR DEPRESSION ; TREATMENT-NAIVE ; THEORETICAL ANALYSIS ; ALZHEIMERS-DISEASE ; CINGULATE CORTEX ; CONNECTIVITY ; 1ST-EPISODE ; PATTERN
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61305018 ; 61432008 ; 61472423 ; 61532006)
WOS研究方向Mathematical & Computational Biology
WOS类目Mathematical & Computational Biology
WOS记录号WOS:000405747000001
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/14844
专题精密感知与控制研究中心_人工智能与机器学习
通讯作者Zhang Wensheng
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.China Acad Chinese Med Sci, Guanganmen Hosp, Dept Radiol, Beijing 100053, Peoples R China
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Wang, Xin,Ren, Yanshuang,Zhang, Wensheng,et al. Depression Disorder Classification of fMRI Data Using Sparse Low-Rank Functional Brain Network and Graph-Based Features[J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE,2017,2017(2017):1.
APA Wang, Xin,Ren, Yanshuang,Zhang, Wensheng,&Zhang Wensheng.(2017).Depression Disorder Classification of fMRI Data Using Sparse Low-Rank Functional Brain Network and Graph-Based Features.COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE,2017(2017),1.
MLA Wang, Xin,et al."Depression Disorder Classification of fMRI Data Using Sparse Low-Rank Functional Brain Network and Graph-Based Features".COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2017.2017(2017):1.
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