# Structure-Aware Trail Bundling for Large DTI Datasets
## 5 Internal Evaluation  
The bundling-and-rendering pipeline introduced in Section 3 offers a wide set of customization options that allow users to generate a large range of visualizations, as illustrated by the images in that section. However, finding one's way in this visual-design space can be challenging. To address this, we first summarize the free parameters of our method in Table 3. For each parameter, we indicate good preset values we found ourselves by experimenting with its settings. When multiple values are listed for a parameter, e.g., the four profiles \(t_{F},t_{S},t_{C},t_{G}\) for the splat shading (Section 3.3.2), this means that there is no evident best value (preset). For instance, one can use these different profiles to create visualizations that emphasize different, equally interesting, aspects of the data, such as DDH-style rendering (which uses \(t_{F}\)) or tube-like rendering with various granularities of the trails (which uses the other three profiles). \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Dataset** & **Trail Count \(|T|\)** & **Sample Points** & **Time/Iteration (ms)** & **Total Time (ms)** \\ \hline Dataset 1 & 50 K & 3.271.979 & 30 & 444 \\ Dataset 2 & 50 K & 1.441.486 & 11 & 170 \\ Dataset 3 & 50 K & 4.145.785 & 20 & 314 \\ \hline Dataset 1 (dense) & 500 K & 32.762.628 & 254 & 3812 \\ Dataset 2 (dense) & 500 K & 12.639.524 & 57 & 858 \\ Dataset 3 (dense) & 500 K & 14.850.241 & 69 & 1029 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: End-to-end execution times of the proposed visualization pipeline for several datasets. \begin{table}
\begin{tabular}{l l l l l l l l l l l l} \hline \hline  & \multicolumn{4}{c}{**DTI Bundling**} & \multicolumn{4}{c}{**Structure-Aware Rendering**} \\ \hline \multicolumn{2}{c}{CUBu} & \multicolumn{2}{c}{Anisotropic} & \multicolumn{2}{c}{Tract} & \multicolumn{2}{c}{Shading} & \multicolumn{2}{c}{Blending} & \multicolumn{2}{c}{Gap filling} & \multicolumn{2}{c}{Outlines} \\ \multicolumn{2}{c}{bundling} & \multicolumn{2}{c}{bundling} & \multicolumn{2}{c}{reseeding} & \multicolumn{2}{c}{(Section 3.3.2)} & \multicolumn{2}{c}{(Section 3.3.3)} & \multicolumn{2}{c}{(Section 3.3.3)} & \multicolumn{2}{c}{(Section 3.3.4)} \\ \multicolumn{2}{c}{(Section 3.2)} & \multicolumn{2}{c}{(Section 3.2.2)} & \multicolumn{2}{c}{(Section 3.2.3)} & & & & & & & \\ \hline \(P_{R}\) & 13 & \(\alpha\) & \(FA\) & \(c_{p}\) & \(\geq\) 0.25 & \(t\) & \(t_{F},t_{G},t_{S},t_{C}\) & usage & peel & \(r_{0}\) & [3,5] & usage & on, off \\ \(P_{N}\) & 15 & \(\alpha_{0}\) & [0,1] & \(c_{l}\) & \(\leq\) 0.2 & **a** & tangent & \(\delta\) & 0.005 & \(\beta\) & 5 & \(\epsilon\) & [3,5] \\ \(\phi\) & 0.25 & & & & & & & \(\alpha\) & 0.1 & & & \\ \(\sigma\) & 1 & & &Figure 12 illustrates the above freedom of parameter choice. Here, we select a relatively small set of 65 K trails and render them, both unbundled and bundled, with four styles (blended lines, DDH, shading, and shading plus outlines), using isotropic bundling (\(\alpha_{0}=1\)). Trails are color-coded on direction. The blended lines style--which corresponds to the classical way DTI trails are rendered in such visualizations--is arguably the most cluttered and does not allow seeing which bundles are in front of others. The DDH style partially alleviates this, but the lack of colors makes visually following bundles hard. Shading offers a good compromise between blended lines and DDH. Finally, shading and outlines make the bundle structures more prominent, but create a more 'loaded' visualization. Separately, we see how isotropic bundling reduces clutter independently on the rendering style, allowing one to peek deeper inside the volume. Figure 13 enriches these insights by showing a larger 250 K trail set. Visualizing the unbundled data (top row) creates high amounts of occlusion. The DDH and shading and outlines styles bring in more structure, but cannot, by themselves, reduce occlusion.