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This is a novel and effective method for visualizing probabilistic tractograms within their anatomical context. This illustrative rendering technique, called fiber stippling, is inspired by visualization standards as found in anatomical textbooks. These illustrations typically show slice-based projections of fiber pathways and are typically hand-drawn. Applying the automatized technique to diffusion tractography, it is possible to demonstrate its expressiveness and intuitive usability as well as a more objective way to present white-matter structure in the human brain.

Scifer is a visualization software designed for the interactive analysis of scientific data.

Scifer currently supports the following application areas:

• Biology: 3D video microscopy, TEM/SEM records of tissue
• Climate research: time series analysis
• Computational fluid dynamics: time series and feature analysis
• Graph analysis
• Multidimensional data analysis

This visualization method combines similarity measures of trajectory shapes and movement-relevant parameters to account for biological questions. In an interactive frame-work, the user can first cluster the cell trajectories according to problem-specific features and interactively validate and analyze the resulting clustering. The flexibility of the similarity metric constitutes a vital feature of this technique. It can be adjusted to describe a large variety of trajectory characteristics and may therefore be adapted to a large variety of task-specific demands. A second feature that proved highly useful is the extension of the visualization to 3D. While most existing techniques only plot the cell lineages in 2D, this method provides the user with different techniques to investigate their data in the natural 3D space.

FluoRender is an interactive tool for neurobiologists to visualize confocal microscopy data in their research. Multiple channels, detailed three-dimensional structures, and time-dependent sequences are the three major features of confocal microscopy data. With these features and usability in mind, we designed and engineered our system, which is now a free package for public download. We present the visualization pipeline and main features of our system for 3D/4D multi-channel confocal data visualization. Our system supports different input formats commonly seen for confocal microscopy. By minimizing pre-processing and optimizing data reading codes, it can read 3D/4D data with minimal latency. It has easy-to-use parameters for volume rendering effects, which are adjusted with real-time speed. It uses several image post-processing methods for detail enhancement, which are applied after volumetric data are rendered, and thus their adjustments are real-time even for 4D sequences. For multi-channel data, our system supports three different blending modes and channel grouping. Users can easily change all the settings and emphasize the most important features.