Haehn Daniel, Franke Loraine, Zhang Fan, Cetin-Karayumak Suheyla, Pieper Steve, O'Donnell Lauren J, Rathi Yogesh
University of Massachusetts Boston.
Harvard Medical School.
Med Image Comput Comput Assist Interv. 2020 Oct;12267:322-332. doi: 10.1007/978-3-030-59728-3_32. Epub 2020 Sep 29.
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.
纤维追踪会生成大量的纤维束成像数据集，其大小可达数十GB，由数百万条流线组成。如此海量的数据需要能够实现高效存储、传输和可视化的格式。我们提出了TRAKO，这是一种基于图形层传输格式（glTF）的新数据格式，可实现即时图形处理和硬件加速处理。我们为顶点、流线以及附加的标量和属性数据集成了一种先进的压缩技术。然后，我们将TRAKO与现有的纤维束成像存储方法进行比较，并对八个数据集进行详细评估。当用于复制先前发表研究中的分析时，TRAKO可实现超过28倍的数据缩减，且不会损失统计显著性。
