Automated identification of epidermal keratinocytes in reflectance confocal microscopy

Abstract. 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( ). Fortytwo

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.

C2011 Society of Photo-Optical Instrumentation Engineers (SPIE).

[DOI: 10.1117/1.3552639]