Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images

Jenkinson, Mark; Bannister, Peter; Brady, Michael; Smith, Stephen

doi:10.1006/nimg.2002.1132

Cited by 11,888Medical Image Segmentation TechniquesAdvanced MRI Techniques and ApplicationsFunctional Brain Connectivity Studies

Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images

Jenkinson, Mark, Bannister, Peter, Brady, Michael, Smith, Stephen·2002·NeuroImage

DOI 10.1006/nimg.2002.1132

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All data sets were corrected for head motion, eddy currents and susceptibility distortions and are, in general, of very high quality.
“All data sets were corrected for head motion, eddy currents and susceptibility distortions and are, in general, of very high quality69–73.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [73]
Participants were excluded for acute suicidality, self- or other-harming behaviour, and excessive motion in the MRI scanner.
“Additionally, participants were excluded in the following cases: acute suicidality (one autistic participant), self- or other-harming behaviour (no participants), excessive motion in the MRI scanner (one autistic participant; defined as mean framewise displacement above 0.55 mm or maximum framewise displacement above 5 mm based on Jenkinson et al., 2002)”
From Are prediction error modifications domain specific in autism but domain general in ADHD? (2025) · cites this paper as Jenkinson et al., 2002
Ground truth registration was defined by way of consistency analysis, in which multiple, independently performed registrations converged to the same result, and that result was judged sensible as assessed by a clinical expert.
“Ground truth registration was defined by way of consistency analysis (Jenkinson et al 2002), in which multiple, independently performed registrations converged to the same result, and that result was judged sensible as assessed by a clinical expert.”
From Robust 3D–2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation (2013) · cites this paper as Jenkinson et al 2002

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doi:10.1006/nimg.2002.1132 Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. M. (2008)
Self-citation
Improved Methods for the Registration and Motion Correction of Brain Images
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. M. (2007)
Self-citation
Optimisation in Robust Linear Registration of Brain Images
Jenkinson, M., & Smith, S. M. (2007)
Self-citation
A global optimisation method for robust affine registration of brain images
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Self-citation
Global Optimization of Medical Image Registration Based on Nonlinear Correlation Measurement
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Authors: Jenkinson, M., Bannister, P., Brady, M., & Smith, S.
Affiliations: John Radcliffe Hospital (GB)
University of Oxford (GB)
Corresponding author: Jenkinson, Mark
ORCID: Jenkinson, Mark
Brady, Michael
Smith, Stephen
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2002-10
Volume: 17
Issue: 2
Pages: 825-841
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1006/nimg.2002.1132
OpenAlex: W2052644075
Cited by: 11,888
References: 18
Citations by year: 2026: 738 · 2025: 819 · 2024: 853 · 2023: 847 · 2022: 824 · 2021: 841 · 2020: 885 · 2019: 743 · 2018: 720 · 2017: 663 · 2016: 663 · 2015: 611 · 2014: 521 · 2013: 477 · 2012: 351
FWCI: 44.51
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Funders: Medical Research Council
Engineering and Physical Sciences Research Council
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords: linear registration, brain image registration, motion correction, optimization methods, local minima, global-local optimization, multi-resolution registration, interpolation methods, registration accuracy
MeSH terms: Acoustic Stimulation, Algorithms, Brain, Computer Simulation, Data Interpretation, Statistical, Humans, Image Interpretation, Computer-Assisted, Models, Neurological, Motion, Photic Stimulation, Reproducibility of Results, Linear Models, Fuzzy Logic

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