Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
نویسندگان
چکیده
منابع مشابه
Identification of disease-related spatial covariance patterns using neuroimaging data.
The scaled subprofile model (SSM)(1-4) is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance pa...
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ژورنال
عنوان ژورنال: Journal of Visualized Experiments
سال: 2013
ISSN: 1940-087X
DOI: 10.3791/50319