Cross-modal coherent registration of whole mouse brains

Lei Qu, Yuanyuan Li, Peng Xie, Lijuan Liu, Yimin Wang, Jun Wu, Yu Liu, Tao Wang, Longfei Li, Kaixuan Guo, Wan Wan, Lei Ouyang, Feng Xiong, Anna C. Kolstad, Zhuhao Wu, Fang Xu, Yefeng Zheng, Hui Gong, Qingming Luo, Guoqiang BiHongwei Dong, Michael Hawrylycz, Hongkui Zeng, Hanchuan Peng

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Recent whole-brain mapping projects are collecting large-scale three-dimensional images using modalities such as serial two-photon tomography, fluorescence micro-optical sectioning tomography, light-sheet fluorescence microscopy, volumetric imaging with synchronous on-the-fly scan and readout or magnetic resonance imaging. Registration of these multi-dimensional whole-brain images onto a standard atlas is essential for characterizing neuron types and constructing brain wiring diagrams. However, cross-modal image registration is challenging due to intrinsic variations of brain anatomy and artifacts resulting from different sample preparation methods and imaging modalities. We introduce a cross-modal registration method, mBrainAligner, which uses coherent landmark mapping and deep neural networks to align whole mouse brain images to the standard Allen Common Coordinate Framework atlas. We build a brain atlas for the fluorescence micro-optical sectioning tomography modality to facilitate single-cell mapping, and used our method to generate a whole-brain map of three-dimensional single-neuron morphology and neuron cell types.

Original languageEnglish
Pages (from-to)111-118
Number of pages8
JournalNature Methods
Issue number1
StatePublished - Jan 2022


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