Scalable and interactive segmentation and visualization of neural processes in EM datasets.
Scalable and interactive segmentation and visualization of neural processes in EM datasets.
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DOI：
10.1109/tvcg.2009.178
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发表时间：
2009-11
影响因子：
5.2
通讯作者：
Whitaker RT
中科院分区：
文献类型：
--
作者：
Jeong WK;Beyer J;Hadwiger M;Vazquez A;Pfister H;Whitaker RT
扫描技术的最新进展提供了高分辨率的EM（电子显微镜）数据集，使神经科学家能够重建神经系统中复杂的神经连接。然而，由于所得到的数据的巨大规模和复杂性，EM数据中的神经过程的分割和可视化通常是一项困难且非常耗时的任务。在本文中，我们提出了NeuroTrace，一种新的EM体积分割和可视化系统，由两部分组成：一个半自动的多相水平集分割与三维跟踪重建的神经过程，和一个专门的体绘制方法的EM体积可视化。它采用视图相关的按需过滤和评估的局部直方图边缘度量，以及在飞行插值和光线投射的隐式表面分割的神经结构。这两种方法都在GPU上实现，以实现交互式性能。NeuroTrace被设计为可扩展到大型数据集和数据并行硬件架构。NeuroTrace与常用的手动EM分割工具的比较表明，我们的交互式工作流程更快，更容易用于重建复杂的神经过程。
Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuroscientists to reconstruct complex neural connections in a nervous system. However, due to the enormous size and complexity of the resulting data, segmentation and visualization of neural processes in EM data is usually a difficult and very time-consuming task. In this paper, we present NeuroTrace, a novel EM volume segmentation and visualization system that consists of two parts: a semi-automatic multiphase level set segmentation with 3D tracking for reconstruction of neural processes, and a specialized volume rendering approach for visualization of EM volumes. It employs view-dependent on-demand filtering and evaluation of a local histogram edge metric, as well as on-the-fly interpolation and ray-casting of implicit surfaces for segmented neural structures. Both methods are implemented on the GPU for interactive performance. NeuroTrace is designed to be scalable to large datasets and data-parallel hardware architectures. A comparison of NeuroTrace with a commonly used manual EM segmentation tool shows that our interactive workflow is faster and easier to use for the reconstruction of complex neural processes.