Emerging neuroimaging datasets (collected with imaging techniques such as electron microscopy, optical microscopy, or X-ray microtomography) describe the location and properties of neurons and their connections at unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. Unfortunately, many neuroscience laboratories lack the computational resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods.

中文翻译：

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面向体积、纳米级神经影像数据集的可重复处理的可扩展框架

新兴的神经影像数据集（通过电子显微镜、光学显微镜或 X 射线显微断层扫描等成像技术收集）以前所未有的规模描述神经元的位置和特性及其连接，有望以新的方式了解大脑。这些用于询问大脑的现代成像技术可以快速积累 GB 到 PB 的结构性大脑成像数据。不幸的是，许多神经科学实验室缺乏处理这种规模数据集的计算资源：计算机视觉工具通常不可移植或不可扩展，并且在再现结果或扩展方法方面存在相当大的困难。