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The FLOWLENS: A Focus-and-Context Visualization Approach for Exploration of Blood Flow in Cerebral Aneurysms

机译:FLOWLENS:脑动脉瘤血流探查的焦点和上下文可视化方法

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Blood flow and derived data are essential to investigate the initiation and progression of cerebral aneurysms as well as their risk of rupture. An effective visual exploration of several hemodynamic attributes like the wall shear stress (WSS) and the inflow jet is necessary to understand the hemodynamics. Moreover, the correlation between focus-and-context attributes is of particular interest. An expressive visualization of these attributes and anatomic information requires appropriate visualization techniques to minimize visual clutter and occlusions. We present the FLOWLENS as a focus-and-context approach that addresses these requirements. We group relevant hemodynamic attributes to pairs of focus-and-context attributes and assign them to different anatomic scopes. For each scope, we propose several FLOWLENS visualization templates to provide a flexible visual filtering of the involved hemodynamic pairs. A template consists of the visualization of the focus attribute and the additional depiction of the context attribute inside the lens. Furthermore, the FLOWLENS supports local probing and the exploration of attribute changes over time. The FLOWLENS minimizes visual cluttering, occlusions, and provides a flexible exploration of a region of interest. We have applied our approach to seven representative datasets, including steady and unsteady flow data from CFD simulations and 4D PC-MRI measurements. Informal user interviews with three domain experts confirm the usefulness of our approach.
机译:血流和衍生数据对于调查脑动脉瘤的发生和进展以及破裂的风险至关重要。必须有效地视觉探索几种血液动力学属性,例如壁切应力(WSS)和流入射流,以了解血液动力学。此外,焦点和上下文属性之间的相关性尤其令人关注。这些属性和解剖学信息的表现力可视化需要适当的可视化技术,以最大程度地减少视觉混乱和遮挡。我们将FLOWLENS作为解决这些需求的焦点和上下文方法提出。我们将相关的血液动力学属性分组为成对的焦点和上下文属性,并将它们分配给不同的解剖范围。对于每个范围,我们提出了几个FLOWLENS可视化模板,以对涉及的血流动力学对提供灵活的视觉过滤。模板包括焦点属性的可视化以及镜头内部上下文属性的其他描述。此外,FLOWLENS支持局部探测,并探索随时间变化的属性。 FLOWLENS可最大程度地减少视觉混乱和遮挡,并提供对感兴趣区域的灵活探索。我们已将我们的方法应用于七个代表性数据集,包括来自CFD模拟和4D PC-MRI测量的稳定和非稳定流量数据。与三位领域专家进行的非正式用户访谈证实了我们方法的有效性。

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