Adaptive 2DCCA based approach for improving spatial specificity of activation detection in functional MRI
The univariate approach without a smoothing filter for detecting activation patterns in functional magnetic resonance imaging (fMRI) data suffers from a low sensitivity due to presence of high noise. The poor performance of univariate methods such as ordinary correlation is due to lack of their ability to take advantage of spatial correlation that exists in fMR images among group of neighboring voxels. To rectify this problem multivariate approaches such as canonical correlation analysis (CCA),...[Show more]
|Collections||ANU Research Publications|
|Source:||2012 International Conference on Digital Image Computing Techniques and Applications, DICTA 2012|
|01_Khalid_Adaptive_2DCCA_based_approach_2012.pdf||209.49 kB||Adobe PDF||Request a copy|
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