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Hierarchical Volume Visualization of Brain Anatomy

机译:大脑解剖结构的层次体积可视化

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Scientific data-sets often come with an inherent hierarchical structure such as functional substructures within organs. In this work we propose a new visualization approach for volume data which is augmented by the explicit representation of hierarchically structured data. The volumetric structures are organized in an interactive hierarchy view. Seamless zooming between data visualization, with volume rendering, and map viewing, for orientation and navigation within the hierarchy, facilitates deeper insight on multiple levels. The map shows all structures, organized in multiple hierarchy levels. Focusing on a selected node allows a visual analysis of a substructure as well as identifying its location in the hierarchy. The visual style of the node in focus, its parent and child nodes are automatically adapted during interaction to emphasize the embedding in the hierarchy. The hierarchy view is linked to a traditional tree view. The value of this new visualization approach is demonstrated on segmented MR1 brain data consisting of hundreds of cortical and sub-cortical structures.
机译:科学数据集通常带有固有的层次结构,例如器官内的功能子结构。在这项工作中,我们提出了一种针对体积数据的新的可视化方法,该方法通过层次结构化数据的显式表示得以增强。体积结构以交互式层次结构视图进行组织。在具有体积渲染的数据可视化和地图查看之间进行无缝缩放,以在层次结构内定向和导航,从而有助于在多个级别上进行更深入的洞察。该地图显示了按多个层次结构层次组织的所有结构。专注于所选节点可以对子结构进行可视化分析,并确定其在层次结构中的位置。焦点节点,其父节点和子节点的视觉样式在交互过程中会自动调整,以强调在层次结构中的嵌入。层次结构视图链接到传统的树形视图。这种新的可视化方法的价值在包含数百个皮质和皮质下结构的MR1大脑分段数据中得到了证明。

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