Anatomy and Embryology

, Volume 210, Issue 4, pp 245–263 | Cite as

Standard atlas space for C57BL/6J neonatal mouse brain

  • Erh-Fang Lee
  • Russell E. Jacobs
  • Ivo Dinov
  • Alex Leow
  • Arthur W. Toga
Original article

Abstract

A standard atlas space with stereotaxic co-ordinates for the postnatal day 0 (P0) C57BL/6J mouse brain was constructed from the average of eight individual co-registered MR image volumes. Accuracy of registration and morphometric variations in structures between subjects were analyzed statistically. We also applied this atlas coordinate system to data acquired using different imaging protocols as well as to a high-resolution histological atlas obtained from separate animals. Mapping accuracy in the atlas space was examined to determine the applicability of this atlas framework. The results show that the atlas space defined here provides a stable framework for image registration for P0 normal mouse brains. With an appropriate feature-based co-registration strategy, the probability atlas can also provide an accurate anatomical map for images acquired using invasive imaging methods. The atlas templates and the probability map of the anatomical labels are available at http://www.loni.ucla.edu/MAP/.

Keywords

Mouse atlas Stereotaxic co-ordinate Feature-based registration Anatomical morphometry MR imaging Gene expression mapping Developing brain 

Abbreviations

P0

Postnatal day 0

SD

Standard deviation

Notes

Acknowledgments

This work was supported by the NIBIB research grant R01 EB002172, the NCRR BIRN grant U24 RR021760, and the Beckman Institute at Caltech. Additional support was provided by the NCRR resource grant P41 RR013642 and the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 RR021813 entitled Center for Computational Biology (CCB). Information on the National Centers for Biomedical Computing can be obtained from <http://nihroadmap.nih.gov/bioinformatics>.

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Erh-Fang Lee
    • 1
  • Russell E. Jacobs
    • 2
  • Ivo Dinov
    • 1
  • Alex Leow
    • 1
  • Arthur W. Toga
    • 1
  1. 1.Department of Neurology, Laboratory of Neuro Imaging, Reed Neurological Research CenterUCLA School of MedicineLos AngelesUSA
  2. 2.Beckman InstituteCalifornia Institute of TechnologyPasadenaUSA

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