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Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain.

David M Young1,2, Siavash Fazel Darbandi1, Grace Schwartz1

  • 1Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, United States.

Elife
|February 11, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational method to create accurate 3D brain atlases from imaging data, significantly reducing artifacts and improving alignment for better quantitative analysis.

Keywords:
3D atlascomputational biologydevelopmental biologyimage processingmousemouse developmentneuroanatomyneurodevelopmentsystems biologytissue clearing

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Medical Imaging

Background:

  • Accurate 3D reference atlases are crucial for interpreting 3D imaging data.
  • Existing methods for 3D atlas generation from 2D data produce artifacts, and manual methods are time-consuming.

Purpose of the Study:

  • To develop a computational approach for constructing artifact-reduced 3D brain atlases.
  • To improve the accuracy and comprehensiveness of 3D atlases for quantitative analysis.

Main Methods:

  • A novel computational pipeline was developed to identify anatomical boundaries in imaging data.
  • These boundaries guide 3D transformations, reducing artifacts and enabling atlas extension to edge regions.
  • The method was applied to the Allen Developing Mouse Brain Atlas (ADMBA) across eight developmental stages.

Main Results:

  • The new method generated more comprehensive and accurate 3D atlases.
  • Validation using 15 whole mouse brains showed qualitative and quantitative improvements.
  • A 37% greater alignment between the atlas and anatomical boundaries was observed.

Conclusions:

  • The developed computational approach significantly reduces artifacts in 3D atlas construction.
  • The MagellanMapper software and 3D ADMBA atlases provide valuable resources for quantitative analysis.
  • These resources facilitate whole-organ analysis across samples and developmental stages.