Name
Title | ||
|---|---|---|
Connectivity-Aware Sectional Visualization of 3D DTI Volumes using Perceptual Flat-Torus Coloring and Edge Rendering. |
Abstract | ||
|---|---|---|
We present two new methods for visualizing cross-sections of 3D diffusion tensor magnetic resonance imaging (DTI) volumes. For each of the methods we show examples of visualizations of the corpus callosum in the midsagittal plane of several normal volunteers. In both methods, we start from points sampled oil a regular grid oil the cross-section and, from each point, generate integral curves in both directions following the principal eigenvector of the underlying diffusion tensor field. We compute an anatomically motivated pairwise distance measure between each pair of integral curves and assemble the measures to create a distance matrix. We next find a set of points in a plane that best preserves the calculated distances that are small-each point in this plane represents one of the original integral curves. Our first visualization method wraps this planar representation onto a flat-torus and then projects that torus into a visible portion of a perceptually uniform color space (L*a*b*). The colors for the paths are used to color the corresponding grid points oil the original cross-section. The resulting image shows larger changes in color where neighboring integral curves differ more. Our second visualization method lays out the grid points oil the cross section and connects the neighboring points with edges that are rendered according to the distances between curves generated from these points. Both methods provide a way to visually segment 2D cross sections of DTI data. Also, a particular contribution of the coloring technique used in our first visualization method is to give a continuous 2D color mapping that provides approximate perceptual uniformity and can be repeated an arbitrary number of times in both directions to increase sensitivity. |
Year | Venue | Field |
|---|---|---|
2006 | Eurographics Technical Report Series | Computer vision,Computer graphics (images),Computer science,Visualization,Artificial intelligence,Flat torus,Rendering (computer graphics),Perception |
DocType | ISSN | Citations |
Conference | 1017-4656 | 3 |
PageRank | References | Authors |
0.39 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Çagatay Demiralp | 1 | 235 | 29.10 |
| Song Zhang | 2 | 642 | 53.89 |
| David F Tate | 3 | 60 | 5.42 |
| Stephen Correia | 4 | 3 | 0.39 |
| David H. Laidlaw | 5 | 1781 | 234.58 |