aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data

Christian J. Niedworok, Alexander P. Y. Brown, M. Jorge Cardoso, Pavel Osten, Sebastien Ourselin, Marc Modat () and Troy W. Margrie ()
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Christian J. Niedworok: MRC National Institute for Medical Research
Alexander P. Y. Brown: MRC National Institute for Medical Research
M. Jorge Cardoso: Translational Imaging Group, Centre for Medical Image Computing, University College London
Pavel Osten: Cold Spring Harbor Laboratory
Sebastien Ourselin: Translational Imaging Group, Centre for Medical Image Computing, University College London
Marc Modat: Translational Imaging Group, Centre for Medical Image Computing, University College London
Troy W. Margrie: MRC National Institute for Medical Research

Nature Communications, 2016, vol. 7, issue 1, 1-9

Abstract: Abstract The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain.

Date: 2016
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DOI: 10.1038/ncomms11879

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