NeuroBlocks - Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects
NeuroBlocks - Visual Tracking of Segmentation and Proofreading for Large Connectomics Projects
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DOI：
10.1109/tvcg.2015.2467441
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发表时间：
2016-01-01
影响因子：
5.2
通讯作者：
Hadwiger, Markus
中科院分区：
文献类型：
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作者：
Al-Awami, Ali K.;Beyer, Johanna;Hadwiger, Markus
在连接组学领域，神经科学家获得纳米分辨率的电子显微镜体积，以重建大脑中神经元的详细布线图。产生的图像体积通常有数百TB大小，需要分割以识别细胞边界，突触和重要的细胞器。然而，单个卷的分割过程非常复杂、耗时，并且通常使用不同的工具集和许多用户来执行。为了解决相关的挑战，本文介绍了NeuroBlocks，这是一种新型的可视化系统，用于跟踪神经科学中非常大的体积分割数据的状态，进度和演变。NeuroBlocks是一个基于Web的多用户应用程序，无缝集成了神经科学家目前用于手动和半自动分割，校对，可视化和分析的各种工具。NeuroBlocks是第一个集成这种异构工具集的系统，为大规模分割的管理、来源、责任和审计提供了关键支持。我们描述了神经块的设计，从分析特定领域的任务，其固有的挑战，以及我们随后的任务抽象和视觉表示。我们展示了我们的设计的基础上，专注于不同的用户角色和他们各自的要求，在一个大型的现实世界的连接组学项目的分割和校对的进展进行跟踪的两个案例研究的实用程序。
In the field of connectomics, neuroscientists acquire electron microscopy volumes at nanometer resolution in order to reconstruct a detailed wiring diagram of the neurons in the brain. The resulting image volumes, which often are hundreds of terabytes in size, need to be segmented to identify cell boundaries, synapses, and important cell organelles. However, the segmentation process of a single volume is very complex, time-intensive, and usually performed using a diverse set of tools and many users. To tackle the associated challenges, this paper presents NeuroBlocks, which is a novel visualization system for tracking the state, progress, and evolution of very large volumetric segmentation data in neuroscience. NeuroBlocks is a multi-user web-based application that seamlessly integrates the diverse set of tools that neuroscientists currently use for manual and semi-automatic segmentation, proofreading, visualization, and analysis. NeuroBlocks is the first system that integrates this heterogeneous tool set, providing crucial support for the management, provenance, accountability, and auditing of large-scale segmentations. We describe the design of NeuroBlocks, starting with an analysis of the domain-specific tasks, their inherent challenges, and our subsequent task abstraction and visual representation. We demonstrate the utility of our design based on two case studies that focus on different user roles and their respective requirements for performing and tracking the progress of segmentation and proofreading in a large real-world connectomics project.