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

By Stamatios N. Sotiropoulos, Saâd Jbabdi, Junqian Xu, Jesper L. R. Andersson, Steen Moeller, E. Auerbach, Matthew F. Glasser, Moisés Hernández, Guillermo Sapiro, Mark Jenkinson and 6 more. NeuroImage, 2013

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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, while 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.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/e3271a97c3ae0aa6da178358ac8f74407602e7dd

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Citations in the corpus

The Human Connectome Project’s Neuroimaging Approach (2016, methodology): “Both of the HCP consortia used customized MRI scanners and pulse sequences to acquire in vivo human diffusion data of unprecedented r e v i e w resolution 5,42–47 .”
Denoising of diffusion MRI using random matrix theory (2016, methodology): “Other examples of targeted image processing tools are the Gibbs correction framework of Kellner et al. (2015) or FSL’s TOPUP and EDDY for EPI and eddy current distortion corrections, respectively (Smith et al., 2004; Sotiropoulos et al., 2013; Glasser et al., 2013).”
Effects of aging on functional and structural brain connectivity☆ (2017, background): “…imaging are just a few developments that have resulted in increased spatial and temporal resolution allowing for more sophisticated analysis techniques that better represent the brain's anatomy and functional dynamics, see (Smith et al., 2013; Sotiropoulos et al., 2013; Ugurbil et al., 2013).”
The Minimal Preprocessing Pipelines for the Human Connectome Project (2013, positive): “However , the use of a monopolar Stejskal–Tanner diffusion scheme and the more powerful gradients increases eddy current-induced distortions, which require the use of a sophisticated approach for correction (Andersson et al., 2012; Sotiropoulos et al., 2013–this issue).”
An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging (2016, methodology): “A multi-band factor of 3 was used, the echo times were optimized for each b-value and were 61, 69, 79 and 90 ms respectively resulting in repetition times of 2, 2.6, 3 and 3.2 s. 3 T HCP data (D) These data have been described in great detail in S. Sotiropoulos et al. (2013).”