论文标题
Trako：有效传输拖拉机数据以进行可视化
TRAKO: Efficient Transmission of Tractography Data for Visualization
论文作者
论文摘要
光纤跟踪产生大型拖拉数据集，这些数据集是数十千兆字节的大小，包括数百万个流线。如此大量的数据需要有效的存储，传输和可视化的格式。我们提出Trako，这是一种基于图形层传输格式（GLTF）的新数据格式，该格式可以立即进行图形和硬件加速处理。我们集成了针对顶点，流线和附加标量和属性数据的最先进的压缩技术。然后，我们将Trako与现有的Tractography Storage方法进行比较，并在八个数据集上提供详细的评估。当用于复制先前发表的研究分析时，Trako可以实现超过28倍的数据减少而不会丧失统计学意义。
Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graphical and hardware-accelerated processing. We integrate a state-of-the-art compression technique for vertices, streamlines, and attached scalar and property data. We then compare TRAKO to existing tractography storage methods and provide a detailed evaluation on eight datasets. TRAKO can achieve data reductions of over 28x without loss of statistical significance when used to replicate analysis from previously published studies.
