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

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

doi:10.1038/s41467-023-41645-4

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

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^*

^*Corresponding author for this work

Macquarie Medical School

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

49 Downloads (Pure)

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.

Original language	English
Article number	5884
Pages (from-to)	1-11
Number of pages	11
Journal	Nature Communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-41645-4
Publication status	Published - 21 Sept 2023

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Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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10.1038/s41467-023-41645-4Licence: CC BY

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AU - Bjerke, Ingvild E.

AU - Puchades, Maja A.

AU - Bjaalie, Jan G.

AU - McMullan, Simon

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

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