J Biomed Opt. 2011 Mar;16(3):030502. doi: 10.1117/1.3552639.
Keratinocytes in skin epidermis, which have bright cytoplasmic contrast and dark nuclear contrast in reflectance confocal microscopy (RCM), were modeled with a simple error function reflectance profile: erf( ). Forty-two example keratinocytes were identified as a training set which characterized the nuclear size a = 8.6±2.8 μm and reflectance gradient b = 3.6±2.1 μm at the nuclear∕cytoplasmic boundary. These mean a and b parameters were used to create a rotationally symmetric erf( ) mask that approximated the mean keratinocyte image. A computer vision algorithm used an erf( ) mask to scan RCM images, identifying the coordinates of keratinocytes. Applying the mask to the confocal data identified the positions of keratinocytes in the epidermis. This simple model may be used to noninvasively evaluate keratinocyte populations as a quantitative morphometric diagnostic in skin cancer detection and evaluation of dermatological cosmetics.
皮肤表皮中的角朊细胞在反射共聚焦显微镜（RCM）下具有明亮的细胞质对比和暗核对比，其模型采用简单的误差函数反射率分布：erf（）。将 42 个示例角朊细胞确定为训练集，其特征在于核大小为 a = 8.6±2.8 μm，核/细胞质边界处的反射率梯度为 b = 3.6±2.1 μm。这些平均值 a 和 b 参数用于创建一个旋转对称的 erf（）掩模，该掩模近似于平均角朊细胞图像。计算机视觉算法使用 erf（）掩模扫描 RCM 图像，识别角朊细胞的坐标。将掩模应用于共聚焦数据可确定表皮中角朊细胞的位置。这种简单的模型可用于非侵入性地评估角朊细胞群体，作为皮肤癌检测和皮肤科化妆品评估的定量形态计量学诊断方法。
