The popularity of mesoscopic whole-brain imaging techniques has increased dramatically, but these techniques generate teravoxel-sized volumetric image data. Visualizing or interacting with these massive data is both necessary and essential in the bioimage analysis pipeline; however, due to their size, researchers have difficulty using typical computers to process them. The existing solutions do not consider applying web visualization and three-dimensional (3D) volume rendering methods simultaneously to reduce the number of data copy operations and provide a better way to visualize 3D structures in bioimage data. Here, we propose webTDat, an open-source, web-based, real-time 3D visualization framework for mesoscopic-scale whole-brain imaging datasets. webTDat uses an advanced rendering visualization method designed with an innovative data storage format and parallel rendering algorithms. webTDat loads the primary information in the image first and then decides whether it needs to load the secondary information in the image. By performing validation on TB-scale whole-brain datasets, webTDat achieves real-time performance during web visualization. The webTDat framework also provides a rich interface for annotation, making it a useful tool for visualizing mesoscopic whole-brain imaging data.

中文翻译：

---

webTDat：一种基于 Web 的实时 3D 中观全脑图像可视化框架

细观全脑成像技术的普及已显着增加，但这些技术会生成 teravoxel 大小的体积图像数据。在生物图像分析流程中，对这些海量数据进行可视化或交互是必要和必不可少的；然而，由于它们的大小，研究人员很难使用典型的计算机来处理它们。现有的解决方案没有考虑同时应用 Web 可视化和三维 (3D) 体积渲染方法来减少数据复制操作的数量，并提供更好的方式来可视化生物图像数据中的 3D 结构。在这里，我们提出了 webTDat，这是一个开源的、基于网络的、实时 3D 可视化框架，用于介观尺度的全脑成像数据集。webTDat 使用先进的渲染可视化方法，采用创新的数据存储格式和并行渲染算法设计。webTDat先加载图片中的主要信息，然后再决定是否需要加载图片中的次要信息。通过对 TB 级全脑数据集进行验证，webTDat 在 Web 可视化过程中实现了实时性能。webTDat 框架还提供了丰富的注释接口，使其成为可视化介观全脑成像数据的有用工具。