Thin, curved structures occur in many volumetric datasets. Their analysis using classical volume rendering is difficult because parts of such structures can bend away or hide behind occluding elements. This problem cannot be fully compensated by effective navigation alone, as structure-adapted navigation in the volume is cumbersome and only parts of the structure are visible in each view. We solve this problem by rendering a spatially transformed view of the volume so that an unobstructed visualization of the entire curved structure is obtained. As a result, simple and intuitive navigation becomes possible. The domain of the spatial transform is defined by a triangle mesh that is topologically equivalent to an open disc and that approximates the structure of interest. The rendering is based on ray-casting, in which the rays traverse the original volume. In order to carve out volumes of varying thicknesses, the lengths of the rays as well as the positions of the mesh vertices can be easily modified by interactive painting under view control. We describe a prototypical implementation and demonstrate the interactive visual inspection of complex structures from digital humanities, biology, medicine, and material sciences. The visual representation of the structure as a whole allows for easy inspection of interesting substructures in their original spatial context. Overall, we show that thin, curved structures in volumetric data can be excellently visualized using ray-casting-based volume rendering of transformed views defined by guiding surface meshes, supplemented by interactive, local modifications of ray lengths and vertex positions.
Bibliographical noteKAUST Repository Item: Exported on 2021-07-01
Acknowledgements: Felix Herter was partially funded by the European Research Council (Project “ELEPHANTINE”, ID 637692). Hans-Christian Hege's work was supported by Deutsche Forschungsgemeinschaft (DFG) through grant CRC 1114 “Scaling Cascades in Complex Systems”, Project (C06) “Multi-scale structure of atmospheric vortices”. Markus Hadwiger was supported by King Abdullah University of Science and Technology (KAUST). We thank Ralf Ziesche (University College London) and Tobias Arlt (Helmholtz-Zentrum Berlin (HZB)) for providing the battery dataset and Marc Etienne, Eve Menei (Musée du Louvre, Paris), Tobias Arlt and Heinz-Eberhard Mahnke (HZB) for providing the papyrus dataset. Ramon Nagesan and Cody Thompson (Museum of Zoology, University of Michigan) are gratefully acknowledged for providing the Armadillo dataset. We also thank Alexander Tack and Felix Ambellan (Zuse Institute Berlin) for their help with the knee dataset and Felix Ambellan for providing the flattening module.
ASJC Scopus subject areas
- Computer Networks and Communications