The minimal preprocessing pipelines for the Human Connectome Project

The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventi...

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Main Authors: Glasser, M, Sotiropoulos, SN, Wilson, J, Coalson, T, Fischl, B, Andersson, J, Xu, J, Jbabdi, S, Webster, M, Polimeni, JR, Van Essen, D, Jenkinson, M
Format: Journal article
Language:English
Published: 2013
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author Glasser, M
Sotiropoulos, SN
Wilson, J
Coalson, T
Fischl, B
Andersson, J
Xu, J
Jbabdi, S
Webster, M
Polimeni, JR
Van Essen, D
Jenkinson, M
author_facet Glasser, M
Sotiropoulos, SN
Wilson, J
Coalson, T
Fischl, B
Andersson, J
Xu, J
Jbabdi, S
Webster, M
Polimeni, JR
Van Essen, D
Jenkinson, M
author_sort Glasser, M
collection OXFORD
description The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3. Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines. © 2013 Elsevier Inc.
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spelling oxford-uuid:c62009e3-9d72-4a21-858b-5d1f6034ca662022-03-27T06:36:02ZThe minimal preprocessing pipelines for the Human Connectome ProjectJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c62009e3-9d72-4a21-858b-5d1f6034ca66EnglishSymplectic Elements at Oxford2013Glasser, MSotiropoulos, SNWilson, JCoalson, TFischl, BAndersson, JXu, JJbabdi, SWebster, MPolimeni, JRVan Essen, DJenkinson, MThe Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3. Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines. © 2013 Elsevier Inc.
spellingShingle Glasser, M
Sotiropoulos, SN
Wilson, J
Coalson, T
Fischl, B
Andersson, J
Xu, J
Jbabdi, S
Webster, M
Polimeni, JR
Van Essen, D
Jenkinson, M
The minimal preprocessing pipelines for the Human Connectome Project
title The minimal preprocessing pipelines for the Human Connectome Project
title_full The minimal preprocessing pipelines for the Human Connectome Project
title_fullStr The minimal preprocessing pipelines for the Human Connectome Project
title_full_unstemmed The minimal preprocessing pipelines for the Human Connectome Project
title_short The minimal preprocessing pipelines for the Human Connectome Project
title_sort minimal preprocessing pipelines for the human connectome project
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