Yet this approach is imperfect: each layer may be accurate on its own, but inevitable mismatches appear between the slices when viewed in 3D or from another angle.Īdvances in microscopy now allow entire organs to be imaged in 3D. For instance, these maps are essential to understand where specific genes are turned on or off, or the spatial organization of various groups of cells over time.įor centuries, atlases have been built by thinly ‘slicing up’ an organ, and then precisely representing each 2D layer. The research community needs precise, reliable 3D atlases of organs to pinpoint where biological structures and processes are located. These resources facilitate whole-organ quantitative analysis between samples and across development. We provide the pipeline as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. We generated imaging data from 15 whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. Anatomical boundaries also allow extension of atlases to complete edge regions. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. 3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation.
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