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Advances in diffusion MRI acquisition and processing in the Human Connectome Project

Sotiropoulos, Stamatios N.; Jbabdi, Saad; Xu, Junqian; Andersson, Jesper L.; Moeller, Steen; Auerbach, Edward J.; Glasser, Matthew F.; Hernandez, Moises; Sapiro, Guillermo; Jenkinson, Mark; Feinberg, David A.; Yacoub, Essa; Lenglet, Christophe; Van Essen, David C.; Ugurbil, Kamil; Behrens, Timothy E.J.

Authors

Saad Jbabdi

Junqian Xu

Jesper L. Andersson

Steen Moeller

Edward J. Auerbach

Matthew F. Glasser

Moises Hernandez

Guillermo Sapiro

Mark Jenkinson

David A. Feinberg

Essa Yacoub

Christophe Lenglet

David C. Van Essen

Kamil Ugurbil

Timothy E.J. Behrens



Abstract

The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013.

Citation

Sotiropoulos, S. N., Jbabdi, S., Xu, J., Andersson, J. L., Moeller, S., Auerbach, E. J., …Behrens, T. E. (2013). Advances in diffusion MRI acquisition and processing in the Human Connectome Project. NeuroImage, 80, https://doi.org/10.1016/j.neuroimage.2013.05.057

Journal Article Type Article
Acceptance Date May 8, 2013
Online Publication Date May 20, 2013
Publication Date Oct 15, 2013
Deposit Date Jul 11, 2018
Publicly Available Date Jul 11, 2018
Journal NeuroImage
Print ISSN 1053-8119
Electronic ISSN 1053-8119
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 80
DOI https://doi.org/10.1016/j.neuroimage.2013.05.057
Public URL http://eprints.nottingham.ac.uk/id/eprint/52877
Publisher URL https://www.sciencedirect.com/science/article/pii/S105381191300551X?via%3Dihub
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





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