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Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach.

, , and . IEEE Trans. Med. Imaging, 36 (7): 1438-1448 (2017)

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Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach., , and . IEEE Trans. Med. Imaging, 36 (7): 1438-1448 (2017)Fixed and Random Effect Analysis of Multi-subject Spatial Activation Maps in Wavelet Domain., , and . IJCNN, page 1389-1392. IEEE, (2006)Discovering true association between multimodal data sets using structured and sparse canonical correlation analysis: A simulation study., , and . ISBI, page 820-823. IEEE, (2016)Controling The False Positive Detection Rate In Fuzzy Clustering of fMRI Data., , and . ISBI, page 388-391. IEEE, (2004)Enhancing reproducibility of fMRI statistical maps using generalized canonical correlation analysis in NPAIRS framework., , , and . NeuroImage, 60 (4): 1970-1981 (2012)Altered topological properties of brain networks in the early MS patients revealed by cognitive task-related fMRI and graph theory., , , , , , and . Biomed. Signal Proc. and Control, (2018)Diffusion kurtosis imaging discriminates patients with white matter lesions from healthy subjects., , , , and . EMBC, page 2796-2799. IEEE, (2011)DCT acquisition and reconstruction of MRI., and . Medical Imaging: Image Processing, volume 3338 of SPIE Proceedings, SPIE, (1998)Simulation of echo planar imaging in MRI: Application to assessment of field inhomogeneity and chemical shift., and . ISSPA, page 1-4. IEEE, (2007)Noise suppression of FMRI time-series in wavelet domain., , and . SIP, page 136-138. IASTED/ACTA Press, (2005)