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UNC-Emory Infant Atlases for Macaque Brain Image Analysis: Postnatal Brain Development through 12 Months

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Last modified
  • 02/20/2025
Type of Material
Authors
    Yundi Shi, University of North CarolinaFrancois Budin, Kitware IncEva Yapuncich, University of North CarolinaAshley Rumple, University of North CarolinaJeffrey T. Young, University of North CarolinaChrista Payne, Emory UniversityXiaodong Zhang, Emory UniversityXiaoping Hu, University of California RiversideJodi Godfrey, Emory UniversityBrittany Howell, University of North CarolinaMaria Sanchez, Emory UniversityMartin A. Styner, University of North Carolina
Language
  • English
Date
  • 2017-01-10
Publisher
  • Frontiers Media
Publication Version
Copyright Statement
  • © 2017 Shi, Budin, Yapuncich, Rumple, Young, Payne, Zhang, Hu, Godfrey, Howell, Sanchez and Styner.
License
Final Published Version (URL)
Title of Journal or Parent Work
ISSN
  • 1662-4548
Volume
  • 10
Start Page
  • 617
End Page
  • 617
Grant/Funding Information
  • his research was supported by the following funding sources MH086633, P50 MH064065, MH070890, HD053000, Roadmap Grant U54 EB005149-01, P50 MH078105 and MH078105-S1, HD055255.
  • NIH grants: UNC Intellectual and Developmental Disabilities Research Center P30 HD03110, MH091645, and Office of Research Infrastructure Programs/OD grant OD11132 (YNPRC Base grant).
Supplemental Material (URL)
Abstract
  • Computational anatomical atlases have shown to be of immense value in neuroimaging as they provide age appropriate reference spaces alongside ancillary anatomical information for automated analysis such as subcortical structural definitions, cortical parcellations or white fiber tract regions. Standard workflows in neuroimaging necessitate such atlases to be appropriately selected for the subject population of interest. This is especially of importance in early postnatal brain development, where rapid changes in brain shape and appearance render neuroimaging workflows sensitive to the appropriate atlas choice. We present here a set of novel computation atlases for structural MRI and Diffusion Tensor Imaging as crucial resource for the analysis of MRI data from non-human primate rhesus monkey (Macaca mulatta) data in early postnatal brain development. Forty socially-housed infant macaques were scanned longitudinally at ages 2 weeks, 3, 6, and 12 months in order to create cross-sectional structural and DTI atlases via unbiased atlas building at each of these ages. Probabilistic spatial prior definitions for the major tissue classes were trained on each atlas with expert manual segmentations. In this article we present the development and use of these atlases with publicly available tools, as well as the atlases themselves, which are publicly disseminated to the scientific community.
Author Notes
Keywords
Research Categories
  • Psychology, General
  • Psychology, Behavioral
  • Biology, Neuroscience

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