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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

DOI :

10.3791/50319-v

June 26th, 2013

June 26th, 2013

15,408 Views

1Center for Neurosciences, The Feinstein Institute for Medical Research

Multivariate techniques including principal component analysis (PCA) have been used to identify signature patterns of regional change in functional brain images. We have developed an algorithm to identify reproducible network biomarkers for the diagnosis of neurodegenerative disorders, assessment of disease progression, and objective evaluation of treatment effects in patient populations.

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Disease related Spatial Covariance Patterns

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