Intra- and inter-rater reliability of digital image analysis for skin color measurement

数字图像分析在肤色测量中的组内和组间信度

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Abstract

BACKGROUND: We determined the intra- and inter-rater reliability of data from digital image color analysis between an expert and novice analyst. METHODS: Following training, the expert and novice independently analyzed 210 randomly ordered images. Both analysts used Adobe(®) Photoshop lasso or color sampler tools based on the type of image file. After color correction with Pictocolor(®) in camera software, they recorded L*a*b* (L*=light/dark; a*=red/green; b*=yellow/blue) color values for all skin sites. We computed intra-rater and inter-rater agreement within anatomical region, color value (L*, a*, b*), and technique (lasso, color sampler) using a series of one-way intra-class correlation coefficients (ICCs). RESULTS: Results of ICCs for intra-rater agreement showed high levels of internal consistency reliability within each rater for the lasso technique (ICC ≥ 0.99) and somewhat lower, yet acceptable, level of agreement for the color sampler technique (ICC = 0.91 for expert, ICC = 0.81 for novice). Skin L*, skin b*, and labia L* values reached the highest level of agreement (ICC ≥ 0.92) and skin a*, labia b*, and vaginal wall b* were the lowest (ICC ≥ 0.64). CONCLUSION: Data from novice analysts can achieve high levels of agreement with data from expert analysts with training and the use of a detailed, standard protocol.

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