Name
Abstract | ||
|---|---|---|
We report empirical study results on the color encoding of ensemble scalar and orientation to visualize diffusion magnetic resonance imaging (DMRI) tubes. The experiment tested six scalar colormaps for average fractional anisotropy (FA) tasks (grayscale, blackbody, diverging, isoluminant-rainbow, extended-blackbody, and coolwarm) and four three-dimensional (3D) spherical colormaps for tract tracing tasks (uniform gray, absolute, eigenmaps, and Boy's surface embedding). We found that extended-blackbody, coolwarm, and blackbody remain the best three approaches for identifying ensemble average in 3D. Isoluminant-rainbow colormap led to the same ensemble mean accuracy as other colormaps. However, more than 50 percent of the answers consistently had higher estimates of the ensemble average, independent of the mean values. The number of hues, not luminance, influences ensemble estimates of mean values. For ensemble orientation-tracing tasks, we found that both Boy's surface embedding (greatest spatial resolution and contrast) and absolute colormaps (lowest spatial resolution and contrast) led to more accurate answers than the eigenmaps scheme (medium resolution and contrast), acting as the uncanny-valley phenomenon of visualization design in terms of accuracy. Absolute colormap broadly used in brain science is a good default spherical colormap. We could conclude from our study that human visual processing of a chunk of colors differs from that of single colors. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TVCG.2019.2898438 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | Field | DocType |
Ensemble visualization,diffusion magnetic resonance imaging,quantitative validation,colormap | Computer vision,Computer graphics (images),Computer science,Scalar (physics),Artificial intelligence | Journal |
Volume | Issue | ISSN |
26 | 9 | 1077-2626 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jian Chen | 1 | 2 | 0.69 |
| Guohao Zhang | 2 | 12 | 4.25 |
| Wesley Chiou | 3 | 1 | 0.35 |
| David H. Laidlaw | 4 | 1781 | 234.58 |
| Alexander P. Auchus | 5 | 14 | 2.37 |