2018/10/18 by Jian Chen, Chen, Jian, Guohao Zhang +7 · 1 citation
Computer Science · Mathematics · Medicine · #Advanced Neuroimaging Techniques and Applications #FOS: Computer and information sciences #Graphics (cs.GR) #Image and Signal Denoising Methods #Morphological variations and asymmetry #cs.GR
paper · pdf · doi:10.48550/arxiv.1810.07882
arxiv created 2018/10/18 · openalex publication_date 2018/10/18 · arxiv updated 2018/10/19 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/31
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) directional encodings for tract tracing tasks (uniform gray, absolute, eigenmap, 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 coloring led to the same ensemble mean accuracy as other colormaps. However, more than 50% of the answers consistently had higher estimates of the ensemble average, independent of the mean values. Hue, not luminance, influences ensemble estimates of mean values. For ensemble orientation-tracing tasks, we found that the Boy's surface embedding (greatest spatial resolution and contrast) and absolute color (lowest spatial resolution and contrast) schemes 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.