Smartphone-based tele-dermatology assumes that colorimetric calibration ensures clinical reliability, yet this remains untested for underrepresented skin phototypes. We investigated whether standard calibration translates to reliable clinical biomarkers using 43,425 images from 965 Korean subjects (Fitzpatrick III-IV) across DSLR, tablet, and smartphone devices. While Linear Color Correction Matrix (CCM) normalization reduced color error by 67-77% -- achieving near-clinical accuracy (Delta E < 2.3) -- this success did not translate to biomarker reliability. We identify a phenomenon termed "color-clinical decoupling": despite perceptual accuracy, the Individual Typology Angle (ITA) showed poor inter-device agreement (ICC = 0.40), while the Melanin Index achieved good agreement (ICC = 0.77). This decoupling is driven by the ITA formula's sensitivity to b* channel noise and is further compounded by anatomical variance. Facial region accounts for 25.2% of color variance -- 3.6x greater than device effects (7.0%) -- challenging the efficacy of single-patch calibration. Our results demonstrate that current colorimetric standards are insufficient for clinical-grade biomarker extraction, necessitating region-aware protocols for mobile dermatology.

翻译：基于智能手机的远程皮肤病学通常假设比色校准能确保临床可靠性，但这一假设在代表性不足的皮肤光型中尚未得到验证。我们使用来自965名韩国受试者（Fitzpatrick III-IV型）的43,425张图像，涵盖数码单反相机、平板电脑和智能手机设备，研究了标准校准是否能转化为可靠的临床生物标志物。虽然线性颜色校正矩阵（CCM）归一化将颜色误差降低了67-77%——达到接近临床的精度（ΔE < 2.3）——但这一成功并未转化为生物标志物的可靠性。我们发现了一种称为“肤色-临床指标解耦”的现象：尽管感知精度很高，个体类型角（ITA）在设备间的一致性较差（ICC = 0.40），而黑色素指数则表现出良好的一致性（ICC = 0.77）。这种解耦是由ITA公式对b*通道噪声的敏感性驱动的，并因解剖学差异而进一步加剧。面部区域占颜色方差的25.2%——是设备效应（7.0%）的3.6倍——这对单点校准的有效性提出了挑战。我们的结果表明，当前的比色标准不足以支持临床级生物标志物的提取，移动皮肤病学需要采用区域感知的校准方案。