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Inter-subject Registration of Functional Images: Do We Need Anatomical Images?

In Echo-Planar Imaging (EPI)-based Magnetic Resonance Imaging (MRI), inter-subject registration typically uses the subject's T1-weighted (T1w) anatomical image to learn deformations of the subject's brain onto a template. The estimated deformation fields are then applied to the subject...

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Autores principales: Dohmatob, Elvis, Varoquaux, Gael, Thirion, Bertrand
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819565/
https://www.ncbi.nlm.nih.gov/pubmed/29497357
http://dx.doi.org/10.3389/fnins.2018.00064
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author Dohmatob, Elvis
Varoquaux, Gael
Thirion, Bertrand
author_facet Dohmatob, Elvis
Varoquaux, Gael
Thirion, Bertrand
author_sort Dohmatob, Elvis
collection PubMed
description In Echo-Planar Imaging (EPI)-based Magnetic Resonance Imaging (MRI), inter-subject registration typically uses the subject's T1-weighted (T1w) anatomical image to learn deformations of the subject's brain onto a template. The estimated deformation fields are then applied to the subject's EPI scans (functional or diffusion-weighted images) to warp the latter to a template space. Historically, such indirect T1w-based registration was motivated by the lack of clear anatomical details in low-resolution EPI images: a direct registration of the EPI scans to template space would be futile. A central prerequisite in such indirect methods is that the anatomical (aka the T1w) image of each subject is well aligned with their EPI images via rigid coregistration. We provide experimental evidence that things have changed: nowadays, there is a decent amount of anatomical contrast in high-resolution EPI data. That notwithstanding, EPI distortions due to B0 inhomogeneities cannot be fully corrected. Residual uncorrected distortions induce non-rigid deformations between the EPI scans and the same subject's anatomical scan. In this manuscript, we contribute a computationally cheap pipeline that leverages the high spatial resolution of modern EPI scans for direct inter-subject matching. Our pipeline is direct and does not rely on the T1w scan to estimate the inter-subject deformation. Results on a large dataset show that this new pipeline outperforms the classical indirect T1w-based registration scheme, across a variety of post-registration quality-assessment metrics including: Normalized Mutual Information, relative variance (variance-to-mean ratio), and to a lesser extent, improved peaks of group-level General Linear Model (GLM) activation maps.
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spelling pubmed-58195652018-03-01 Inter-subject Registration of Functional Images: Do We Need Anatomical Images? Dohmatob, Elvis Varoquaux, Gael Thirion, Bertrand Front Neurosci Neuroscience In Echo-Planar Imaging (EPI)-based Magnetic Resonance Imaging (MRI), inter-subject registration typically uses the subject's T1-weighted (T1w) anatomical image to learn deformations of the subject's brain onto a template. The estimated deformation fields are then applied to the subject's EPI scans (functional or diffusion-weighted images) to warp the latter to a template space. Historically, such indirect T1w-based registration was motivated by the lack of clear anatomical details in low-resolution EPI images: a direct registration of the EPI scans to template space would be futile. A central prerequisite in such indirect methods is that the anatomical (aka the T1w) image of each subject is well aligned with their EPI images via rigid coregistration. We provide experimental evidence that things have changed: nowadays, there is a decent amount of anatomical contrast in high-resolution EPI data. That notwithstanding, EPI distortions due to B0 inhomogeneities cannot be fully corrected. Residual uncorrected distortions induce non-rigid deformations between the EPI scans and the same subject's anatomical scan. In this manuscript, we contribute a computationally cheap pipeline that leverages the high spatial resolution of modern EPI scans for direct inter-subject matching. Our pipeline is direct and does not rely on the T1w scan to estimate the inter-subject deformation. Results on a large dataset show that this new pipeline outperforms the classical indirect T1w-based registration scheme, across a variety of post-registration quality-assessment metrics including: Normalized Mutual Information, relative variance (variance-to-mean ratio), and to a lesser extent, improved peaks of group-level General Linear Model (GLM) activation maps. Frontiers Media S.A. 2018-02-14 /pmc/articles/PMC5819565/ /pubmed/29497357 http://dx.doi.org/10.3389/fnins.2018.00064 Text en Copyright © 2018 Dohmatob, Varoquaux and Thirion. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Dohmatob, Elvis
Varoquaux, Gael
Thirion, Bertrand
Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title_full Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title_fullStr Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title_full_unstemmed Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title_short Inter-subject Registration of Functional Images: Do We Need Anatomical Images?
title_sort inter-subject registration of functional images: do we need anatomical images?
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819565/
https://www.ncbi.nlm.nih.gov/pubmed/29497357
http://dx.doi.org/10.3389/fnins.2018.00064
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