Curves and surfaces for CAGD: a practical guide
Curves and surfaces for CAGD: a practical guide
Proceedings of the 12th Eurographics Workshop on Rendering Techniques
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Light scattering from human hair fibers
ACM SIGGRAPH 2003 Papers
Compression, segmentation, and modeling of filamentary volumetric data
SM '04 Proceedings of the ninth ACM symposium on Solid modeling and applications
IEEE Transactions on Information Technology in Biomedicine
Visualizing Whole-Brain DTI Tractography with GPU-based Tuboids and LoD Management
IEEE Transactions on Visualization and Computer Graphics
Effective techniques to visualize filament-surface relationships
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU.We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.