A review of multivariate methods for multimodal fusion of brain imaging data.
A review of multivariate methods for multimodal fusion of brain imaging data.
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DOI：
10.1016/j.jneumeth.2011.10.031
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发表时间：
2012-02-15
影响因子：
3
通讯作者：
Calhoun, Vince D.
中科院分区：
文献类型：
--
作者：
Sui, Jing;Adali, Tuelay;Yu, Qingbao;Chen, Jiayu;Calhoun, Vince D.
各种神经成像技术的发展正在迅速改善脑功能/结构的测量。然而，尽管个体模态有所改进，但越来越清楚的是，最有效的研究方法将利用多模态融合，它利用了每个模态提供有限大脑视图的事实。多模态融合的目标是在联合分析中利用每种模态的优势，而不是单独分析每种模态。这是一项更复杂的工作，必须更仔细地对待，并应制定有效的方法，从有限数量的高维数据中得出普遍和有效的结论。基于独立成分分析（ICA）、典型相关分析（CCA）和偏最小二乘（PLS）等统计方法，在该领域进行了大量的研究。在这篇综述文章中，我们调查了之前报告中出现的一些多变量方法，这些方法在有或没有先验信息的情况下进行，可能对识别潜在的脑部疾病生物标志物有用。我们还讨论了每种方法可能的优势和局限性，并回顾了它们在脑成像数据中的应用。
The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multimodal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous reports, which are performed with or without prior information and may have utility for identifying potential brain illness biomarkers. We also discuss the possible strengths and limitations of each method, and review their applications to brain imaging data.
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DOI：
10.1109/titb.2008.923773
发表时间：
2009-09-01
影响因子：
--
作者：
Calhoun, Vince D.;Adali, Tuelay
通讯作者：
Adali, Tuelay
影响因子：
2.5
作者：
Babiloni, F;Mattia, D;Cincotti, F
通讯作者：
Cincotti, F
影响因子：
5.7
作者：
Beckmann, CF;Smith, SM
通讯作者：
Smith, SM
DOI：
10.1136/jnnp.2007.125401
发表时间：
2008-05
期刊：
Journal of neurology, neurosurgery, and psychiatry
影响因子：
--
作者：
Hamandi K;Powell HW;Laufs H;Symms MR;Barker GJ;Parker GJ;Lemieux L;Duncan JS
通讯作者：
Duncan JS
影响因子：
5.7
作者：
Calhoun VD;Liu J;Adali T
通讯作者：
Adali T