Automated quantitative analysis of coat and skin coloration in laboratory animals

Introduction. Analysis of animal coat and skin coloration can be used as an auxiliary method for assessment of various conditions and processes that are accompanied by changes in coloration, intensity, proportion of coat colors or areas covered by fur, undercoat, and skin. Performing coloration analysis in preclinical studies requires new straightforward, fast, and easily standardizable digital methods that yield reproducible data suitable for statistical processing.

Aim. In this work, we aimed to develop and test a novel algorithm for quantitative analysis of coat and skin coloration in laboratory animals using R programming language.

Materials and methods. To analyse fur coloration, we used digital photographs of female guinea pigs, one bicolor and one calico, that were taken under artificial lighting against a plain contrasting background. Analysis of fur and skin area proportion was carried out re-using photographs of a male mouse with depilation alopecia model, which were obtained during a previously published preclinical study. Colorimetric image analysis was performed by hierarchical k-means color clustering in RGB space and cluster area calculation using the recolorize v0.2.0 function package for R v4.2.3 with RStudio v2025.05.0.

Results and discussion. The algorithm for colorimetric analysis included 3 steps: 1) preprocessing images and masking the background; 2) hierarchical color clustering and reclustering; 3) calculating absolute and relative color cluster areas. Using the described algorithm, we found the color area proportion to be 46.1 % agouti vs. 53.9 % yellow for the bicolor guinea pig, and 9.1 % red vs. 19.6 % white vs. 71.3 % black, for the calico one. In the male mouse subjected to depilation, we characterized the dynamics of proportion between areas of hairless skin and skin with regrown hair across a 28 day-long period. We found a decrease in relative of hairless skin area between the 0^th, 9^th, and 17^th days post-depilation from 8.7 to 7.4 % and to 0.0 %, respectively (p < 0.05 for 17^th day vs. 0^th and 9^th).

Сonclusion. In this work, we described and tested on model photographs an algorithm for analysis of coat and skin coloration using hierarchical color clustering. The algorithm does not require the use of specialized software, is fast and straightforward, and can be employed for batch image processing to obtain quantitative data for further statistical analysis.

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