Recent technological advancements have facilitated the imaging of specific neuronal populations at the single-axon level across the mouse brain. However, the digital reconstruction of neurons from a large dataset requires months of manual effort using the currently available software. In this study, we develop an open-source software called GTree (global tree reconstruction system) to overcome the above-mentioned problem. GTree offers an error-screening system for the fast localization of submicron errors in densely packed neurites and along with long projections across the whole brain, thus achieving reconstruction close to the ground truth. Moreover, GTree integrates a series of our previous algorithms to significantly reduce manual interference and achieve high-level automation. When applied to an entire mouse brain dataset, GTree is shown to be five times faster than widely used commercial software. Finally, using GTree, we demonstrate the reconstruction of 35 long-projection neurons around one injection site of a mouse brain. GTree is also applicable to large datasets (10 TB or higher) from various light microscopes.

最近的技术进步促进了小鼠大脑单轴突水平特定神经元群体的成像。但是，使用当前可用的软件从大型数据集中进行神经元的数字重建需要数月的人工。在这项研究中，我们开发了一个名为GTree（全局树重构系统）的开源软件来克服上述问题。GTree提供了一个错误筛查系统，可以快速定位密集堆积的神经突中的亚微米错误，并可以在整个大脑中进行长距离投射，从而实现接近地面真相的重建。此外，GTree集成了我们以前的一系列算法，以显着减少人工干扰并实现高级自动化。当应用于整个小鼠大脑数据集时，GTree被证明比广泛使用的商业软件快五倍。最后，使用GTree，我们演示了小鼠脑部一个注射部位周围35个长投影神经元的重建。GTree还适用于来自各种光学显微镜的大型数据集（10 TB或更高）。