Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
Semi-automatic generation of transfer functions for direct volume rendering
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Image-based transfer function design for data exploration in volume visualization
Proceedings of the conference on Visualization '98
Volume rendering of fine details within medical data
Proceedings of the conference on Visualization '01
CPR: curved planar reformation
Proceedings of the conference on Visualization '02
Tissue Classification Based on 3D Local Intensity Structures for Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Multidimensional Transfer Functions for Interactive Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
The VesselGlyph: Focus & Context Visualization in CT-Angiography
VIS '04 Proceedings of the conference on Visualization '04
Silhouette maps for improved texture magnification
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
IEEE Transactions on Visualization and Computer Graphics
Small vessel enhancement in MRA images using local maximum mean processing
IEEE Transactions on Image Processing
Viewpoint selection for angiographic volume
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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Direct volume rendering (DVR) is an effective way to visualize 3D vascular images for diagnosis of different vascular pathologies and planning of surgical treatments. Angiograms are typically noisy, fuzzy, and contain thin vessel structures. Therefore, some kinds of enhancements are usually needed before direct volume rendering can start. However, without visualizing the 3D structures in angiograms, users may find it difficult to select appropriate parameters and assess the effectiveness of the enhancement results. In addition, traditional enhancement techniques cannot easily separate the vessel voxels from other contextual structures with the same or very similar intensity. In this paper, we propose a framework to integrate enhancement and direct volume rendering into one visualization pipeline using multi-dimensional transfer function tailored for visualizing the curvilinear and line structures in angiograms. Furthermore, we present a feature preserving interpolation method to render very thin vessels which are usually missed using traditional approaches. To ease the difficulty in vessel selection, a MIP-guided method is suggested to assist the process.