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Pushing the limits of in vivo diffusion MRI for the Human Connectome Project., , , , , , , , , and 14 other author(s). NeuroImage, (2013)Head motion during MRI acquisition reduces gray matter volume and thickness estimates., , , , , and . NeuroImage, (2015)Maximum Likelihood Estimators in Magnetic Resonance Imaging., , and . IPMI, volume 4584 of Lecture Notes in Computer Science, page 434-445. Springer, (2007)Neurofeedback using functional spectroscopy., , , , , and . Int. J. Imaging Syst. Technol., 24 (2): 138-148 (2014)Investigating the Capability to Resolve Complex White Matter Structures with High b-Value Diffusion Magnetic Resonance Imaging on the MGH-USC Connectom Scanner., , , , , , , , , and 3 other author(s). Brain Connectivity, 4 (9): 718-726 (2014)Prospective motion correction with volumetric navigators (vNavs) reduces the bias and variance in brain morphometry induced by subject motion., , , , , and . NeuroImage, (2016)3D GABA imaging with real-time motion correction, shim update and reacquisition of adiabatic spiral MRSI., , , , , , , , , and 2 other author(s). NeuroImage, (2014)Effects of Resolution and Registration Algorithm on the Accuracy of EPI vNavs for Real Time Head Motion Correction in MRI., , , and . CVPR Workshops, page 583-591. IEEE Computer Society, (2016)MGH-USC Human Connectome Project datasets with ultra-high b-value diffusion MRI., , , , , , , , , and 14 other author(s). NeuroImage, (2016)Using Human and Model Performance to Compare MRI Reconstructions., and . IEEE Trans. Med. Imaging, 25 (11): 1510-1517 (2006)