Dimensionality of ICA in Resting-State fMRI Investigated by Feature Optimized Classification of Independent Components with SVM

Dimensionality of ICA in Resting-State fMRI Investigated by Feature Optimized Classification of Independent Components with SVM

Different machine learning algorithms have recently been used for assisting automated classification of independent component analysis (ICA) results from resting-state fMRI data. The success of this approach relies on identification of artifact components and meaningful functional networks. A limiti...

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Bibliographic Details
Main Authors: Yanlu eWang, Tie-Qiang eLi
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-05-01
Series:Frontiers in Human Neuroscience
Subjects:
Functional Neuroimaging
Magnetic Resonance Imaging
machine learning
Independent Component Analysis
image processing
Pattern Classification
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00259/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00259/full

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