ColorI-DT : An open-source tool for the quantitative evaluation of differences in microscopy color images

This is the authors' abstract. We don't add key points for this paper.

In several fields, quantitatively comparing color images is crucial. For instance, this is important in Histopathology, where different microscopes/cameras are typically used for visualizing patient samples by causing significant color variation. No ground-truth metric exists for estimating differences between pairs of color images. A range of possible solutions is available but there is no existing open-source tool that allow clinicians and researchers to apply these metrics to microscopy images through an intuitive, easy-to-use software. In this work, we developed Color Image Difference Tool ( ColorI-DT ), an open-source tool for measuring quantitative differences between color images of the same subject acquired under different settings. Thanks to a user-friendly graphical user interface, it allows the selection of a pair of color images and a metric from a list of available options, and produces an output 2D pixel-wise color difference matrix between corresponding pixels in the input images. The metrics currently implemented are: ( 1 ) Euclidean Δ E ; ( 2 ) International Commission on Illumination (CIE) 76 (Luv); ( 3 ) CIE76 (Lab); ( 4 ) CIE94; ( 5 ) CIE00; ( 6 ) Colour Measurement Committee (CMC). To demonstrate how to use the tool, microscopy images with a predominant color in the red, green, or blue channel were used. In particular, we checked which among the 6 metrics displays the most predictable and linear behavior in the case of controlled primary color alterations. For more pronounced color adjustments, a qualitative comparison would be likely sufficient for analyzing color differences, as a quantitative tool may become unreliable due to the inherent limitations of the implemented metrics.