Adaptive Surface Visualization of Vessels with Embedded Blood Flow Based on the Suggestive Contour Measure

Abstract

The investigation of hemodynamic information for the assessment of cardiovascular diseases (CVD) has increased in recent years. Improved flow measuring modalities and computational fluid dynamics (CFD) simulations are suitable to provide domain experts with reliable blood flow information. For a visual exploration of the flow information domain experts are used to investigate the flow information combined with its enclosed vessel anatomy. Since the flow is spatially embedded in the surrounding vessel surface, occlusion problems have to be resolved that include a meaningful visual reduction of the vessel surface but still provide important anatomical features. We accomplish this by applying an adaptive surface visualization inspired by the suggestive contour measure. Our approach combines several visualization techniques to improve the perception of surface shape and depth. Thereby, we ensure appropriate visibility of the embedded flow information, which can be depicted with established or advanced flow visualization techniques. We apply our approach to cerebral aneurysms and aortas with simulated and measured blood flow. In an informal user feedback with nine domain experts, we confirm the advantages of our approach compared with existent methods, e.g., semi-transparent surface rendering.