Evaluation of volume-based and surface-based brain image registration methods
Open accessAbstract
Establishing correspondences across brains for the purposes of comparison and group analysis is almost universally done by registering images to one another either directly or via a template. However, there are many registration algorithms to choose from. A recent evaluation of fully automated nonlinear deformation methods applied to brain image registration was restricted to volume-based methods. The present study is the first that directly compares some of the most accurate of these volume registration methods with surface registration methods, as well as the first study to compare registrations of whole-head and brain-only (de-skulled) images. We used permutation tests to compare the overlap or Hausdorff distance performance for more than 16,000 registrations between 80 manually labeled brain images. We compared every combination of volume-based and surface-based labels, registration, and evaluation. Our primary findings are the following: 1. de-skulling aids volume registration methods; 2. custom-made optimal average templates improve registration over direct pairwise registration; and 3. resampling volume labels on surfaces or converting surface labels to volumes introduces distortions that preclude a fair comparison between the highest ranking volume and surface registration methods using present resampling methods. From the results of this study, we recommend constructing a custom template from a limited sample drawn from the same or a similar representative population, using the same algorithm used for registering brains to the template.
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Normalization to a study-specific template offers superior registration over direct pairwise methods.
“Normalization to a study-specific template offers superior registration over direct pairwise methods (Klein et al., 2010).”
From Neural Correlates of Long-Term Memory Enhancement Following Retrieval Practice (2021) · cites this paper as Klein et al., 2010
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- Authors
- Klein, A., Ghosh, S. S., Avants, B., Yeo, B. T. T., Fischl, B., Ardekani, B., Gee, J. C., Mann, J. J., & Parsey, R. V.
- Affiliations
- New York State Psychiatric Institute (US)
- Massachusetts Institute of Technology (US)
- University of Pennsylvania (US)
- Harvard University (US)
- Nathan Kline Institute for Psychiatric Research (US)
- Corresponding author
- Klein, Arno
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 51
- Issue
- 1
- Pages
- 214-220
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2862732
- OpenAlex
- W2099869863
- Cited by
- 255
- References
- 25
- Citations by year
- 2026: 7 · 2025: 6 · 2024: 9 · 2023: 16 · 2022: 12 · 2021: 21 · 2020: 19 · 2019: 14 · 2018: 15 · 2017: 22 · 2016: 18 · 2015: 20 · 2014: 24 · 2013: 20 · 2012: 17
- FWCI
- 19.22
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Center for Research Resources (P41-RR14075, BIRN002, U24 RR021382)
- National Institute on Aging (AG02238)
- National Institutes of Health (U54 EB005149, R01 MH084029)
- National Institute of Neurological Disorders and Stroke (R01 NS052585-01)
- Ellison Medical Foundation
- National Institute of Biomedical Imaging and Bioengineering (R01 EB006758, R03 EB008201, R03 EB008673)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- brain image registration, surface registration, template-based registration, Hausdorff distance, registration evaluation, permutation tests, label overlap, nonlinear deformation
- MeSH terms
- Adult, Algorithms, Brain, Female, Head, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Organ Size, Software, Imaging, Three-Dimensional, Young Adult
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