Objectives:

To quantitatively evaluate the performance of the most used colormaps in image display using perceptual metrics and to what extent these measures are congruent with the true intensity or uptake of pixels at different levels of defect severity in simulated cardiac images.

Methods:

Six colormaps, labeled “Gray”, “Thermal”, “Cool”, “CEqual”, “Siemens” and “S Pet” extracted from FIJI ImageJ software are included. Colormap data are converted from the red, green, blue color space to CIELAB. Perceptual metrics for measuring “color difference” were calculated, including difference (ΔE⁷⁶) and “speed”. The pairwise color difference in every two levels or entries is visualized in a 2-dimensional “heatmap distance matrix” for each colormap. Curves are plotted for each colormap and compared. In addition, to apply this technique to clinical images, simulated short-axis cardiac slices with incremental defect severity (10% grading) were employed. The circumferential profile curves of true pixel intensity, lightness or luminance, and color difference are plotted simultaneously for each defect severity to visualize the concordance of the three curves in various colormaps.

Results:

In 0% defect, all the curves are at the highest level, except for “s pet”, in that the lightness is not at its maximum value. In the phantom with 10% defect (or 90% of maximum value), discrepancies among curves appear. In “Siemens”, the ΔE⁷⁶ drops sharply. In “Siemens” colormap, the ΔE⁷⁶ drops sharply. In 80% defect, ΔE⁷⁶ curve, in “gray” colormap drops more slowly than other curves of other colormaps. In “s pet”, lightness curve rises paradoxically, although the count intensity and ΔE⁷⁶ curve match. In 70% defect, again, the curves are in good agreement in “thermal”, “Siemens” and “cequal”. However, a consistent lag exists in “gray”. Up to 50% defect, curves maintain their expected pattern, but in defects more severe than 40%, lightness and ΔE⁷⁶ curves in “cool” and “cequal” rise paradoxically, and in “thermal”, they start to slow down in descent. In “Siemens”, falling pattern of the three curves continues. For “s pet” colormap, an erratic pattern of lightness and ΔE⁷⁶ curves exists.

Conclusion:

Of 6 colormaps investigated for estimating defect severity, “grayscale” is less favorable than others and “thermal” performs slightly better. “s pet” or rainbow, which is used traditionally by many practitioners, is strongly discouraged. The “Siemens” colormap suffers from decreased discriminating power in the range of mild to moderate/severe. In contrast, the “cool” and “cequal” colormaps outperform the other colormaps employed in this study to some extent, although they have some shortcomings.

Keywords: Colormap, look-up table, performance, perceptual metric, image display, quantitative analysis