The study and visualization of vascular structures, using 3D models obtained from medical data, is an active field of research. Illustrative visualizations have been applied to this domain in multiple ways. Researchers have tried to make the geometric properties of vasculature more comprehensive and to augment the surface with representations of multivariate clinical data. Techniques that head beyond the application of color-maps or simple shading approaches require a sort of surface

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... ation, i.e., texture coordinates, in order to overcome locality. When extracting 3D models, the computation of texture coordinates on the mesh is not always part of the data processing pipeline. We combine existing techniques to a simple, yet effective, parameterization approach that is suitable for tree-like structures. The parameterization is done w.r.t. to a pre-defined source vertex. For this, we present an automatic algorithm, that detects the root of a tree-structure. The parameterization is partly done in screen-space and recomputed per frame. However, the screen-space computation comes with positive features that are not present in object-space approaches. We show how the resulting texture coordinates can be used for varying hatching, contour parameterization, the display of decals, as an additional depth cue and feature extraction.