Comparison of template registration methods for multi-site meta-analysis of brain morphometry

Joshua Faskowitz; Greig I. de Zubicaray; Katie L. McMahon; Margaret J. Wright; Paul M. Thompson; Neda Jahanshad

doi:10.1117/12.2217370

29 March 2016 Comparison of template registration methods for multi-site meta-analysis of brain morphometry

Joshua Faskowitz, Greig I. de Zubicaray, Katie L. McMahon, Margaret J. Wright, Paul M. Thompson, Neda Jahanshad

Proceedings Volume 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging; 978822 (2016) https://doi.org/10.1117/12.2217370
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Neuroimaging consortia such as ENIGMA can significantly improve power to discover factors that affect the human brain by pooling statistical inferences across cohorts to draw generalized conclusions from populations around the world. Voxelwise analyses such as tensor-based morphometry also allow an unbiased search for effects throughout the brain. Even so, such consortium-based analyses are limited by a lack of high-powered methods to harmonize voxelwise information across study populations and scanners. While the simplest approach may be to map all images to a single standard space, the benefits of cohort-specific templates have long been established. Here we studied methods to pool voxel-wise data across sites using templates customized for each cohort but providing a meaningful common space across all studies for voxelwise comparisons. As non-linear 3D MRI registrations represent mappings between images at millimeter resolution, we need to consider the reliability of these mappings. To evaluate these mappings, we calculated test-retest statistics on the volumetric maps of expansion and contraction. Further, we created study-specific brain templates for ten T1-weighted MRI datasets, and a common space from four study-specific templates. We evaluated the efficacy of using a two-step registration framework versus a single standard space. We found that the two-step framework more reliably mapped subjects to a common space.

Citation Download Citation

Joshua Faskowitz, Greig I. de Zubicaray, Katie L. McMahon, Margaret J. Wright, Paul M. Thompson, and Neda Jahanshad "Comparison of template registration methods for multi-site meta-analysis of brain morphometry", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 978822 (29 March 2016); https://doi.org/10.1117/12.2217370

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
14 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image registration

Brain

Brain mapping

Reliability

Neuroimaging

Signal to noise ratio

Statistical analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years