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Groupwise whole-brain parcellation from resting-state fMRI data for network node identification., , , and . NeuroImage, (2013)Graph-theory based parcellation of functional subunits in the brain from resting-state fMRI data., , and . NeuroImage, 50 (3): 1027-1035 (2010)The (in)stability of functional brain network measures across thresholds., , , , and . NeuroImage, (2015)An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks., , , , and . NeuroImage, (2018)Detection and Segmentation of Concealed Objects in Terahertz Images., , , , and . IEEE Trans. Image Processing, 17 (12): 2465-2475 (2008)Multiscale Analysis of fMRI Data with Mixture of Gaussian Densities., and . ISBI, page 1175-1178. IEEE, (2004)Considering factors affecting the connectome-based identification process: Comment on Waller et al., , , , , and . NeuroImage, (2018)Analysis of Event-Related fMRI Data Using Diffusion Maps., and . IPMI, volume 3565 of Lecture Notes in Computer Science, page 652-663. Springer, (2005)Ten simple rules for predictive modeling of individual differences in neuroimaging., , , , , , , , , and 3 other author(s). NeuroImage, (2019)Multisite reliability of MR-based functional connectivity., , , , , , , , , and 11 other author(s). NeuroImage, (2017)