Ministry of Education Key Laboratory of Intelligent Computation & Signal Processing, Information Materials and Intelligent Sensing Laboratory of Anhui Province, School of Electronics and Information Engineering, Anhui University, Hefei, China.
SEU-ALLEN Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, China.
Nat Methods. 2022 Jan;19(1):111-118. doi: 10.1038/s41592-021-01334-w. Epub 2021 Dec 9.
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.
最近的全脑图谱项目正在使用诸如双光子断层扫描、荧光显微光学切片断层扫描、光片荧光显微镜、同步飞行扫描和读出的容积成像或磁共振成像等方式来收集大规模的三维图像。将这些多维全脑图像配准到标准图谱对于表征神经元类型和构建大脑连接图至关重要。然而,由于大脑解剖结构的固有变化以及不同的样本制备方法和成像方式产生的伪影,跨模态图像配准具有挑战性。我们引入了一种跨模态配准方法 mBrainAligner,该方法使用相干标记映射和深度神经网络将整个小鼠大脑图像配准到标准 Allen 公共坐标框架图谱。我们构建了一个荧光显微光学切片断层扫描模式的大脑图谱,以促进单细胞映射,并使用我们的方法生成了三维单细胞形态和神经元细胞类型的全脑图谱。