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DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas

Author

Listed:
  • Harry Carey

    (Macquarie University
    University of Oslo)

  • Michael Pegios

    (Macquarie University)

  • Lewis Martin

    (OpenBench)

  • Chris Saleeba

    (Macquarie University)

  • Anita J. Turner

    (Macquarie University)

  • Nicholas A. Everett

    (University of Sydney)

  • Ingvild E. Bjerke

    (University of Oslo)

  • Maja A. Puchades

    (University of Oslo)

  • Jan G. Bjaalie

    (University of Oslo)

  • Simon McMullan

    (Macquarie University)

Abstract

Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.

Suggested Citation

  • Harry Carey & Michael Pegios & Lewis Martin & Chris Saleeba & Anita J. Turner & Nicholas A. Everett & Ingvild E. Bjerke & Maja A. Puchades & Jan G. Bjaalie & Simon McMullan, 2023. "DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41645-4
    DOI: 10.1038/s41467-023-41645-4
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    References listed on IDEAS

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