In biomedical computing the need for visualization methods of the human vascular system has been triggered by recent advances in image acquisition technology. In this paper we describe a number of approaches for the three-dimensional display of vessels from volumetric datasets. Our approaches are based on the analysis of the deficiencies of the Maximum Intensity Projection algorithm, which today is the state-of-the-art technique for vascular display, and takes into account different diagnostic and therapeutic situations. For the qualitative as well as quantitative evaluation of the major vessels, e.g., the carotids, a model-driven Computer Vision method to segment, reconstruct and render the vascular tree surface including branches is presented. For the assessment of smaller vessels a Pattern Recognition technique for contrast enhancement of line-like structures is introduced. It serves as a preprocessing step prior to the application of a volume-rendering algorithm that consists of an advanced maximum projection scheme with depth-cueing. The integrated 3D display of soft-tissue surfaces with adjacent vasculature, as required, e.g., for neurosurgery planning, is enabled by a raycaster, simultaneously rendering and merging two volume datasets. We emphasize the clinical relevance of techniques for explorative volume data analysis by a walkthrough example. The paper demonstrates the necessity of incorporating Computer Vision and Pattern Recognition methodologies into the Scientific Visualization pipeline for biomedical imaging. © 1994.
Ehricke, H. H., Donner, K., Koller, W., & Straßer, W. (1994). Visualization of vasculature from volume data. Computers and Graphics, 18(3), 395–406. https://doi.org/10.1016/0097-8493(94)90040-X