Automatic measurement of epidermal thickness from optical coherence tomography images using a new algorithm

Background/purpose: Optical coherence tomography (OCT) is an imaging system that enables in vivo epidermal thickness (ET) measurement. In order to use OCT in large-scale clinical studies, automatic algorithm detection of the dermo-epidermal junction (DEJ) is needed. This may be difficult due to image noise from optical speckle, which requires specific image treatment procedures to reduce this. In the present work, a description of the position of the DEJ is given, and an algorithm for boundary detection is presented. Methods: Twenty-nine images were taken from the skin of normal healthy subjects, from five different body sites. Seven expert assessors were asked to trace the DEJ for ET measurement on each of the images. The variability between experts was compared with a new image processing method. Results: Between-expert variability was relatively low with a mean standard deviation of 3.4 mm. However, local positioning of the DEJ between experts was often different. The described algorithm performed adequately on all images. ET was automatically measured with a precision of <5 mu m compared with the experts on all sites studied except that of the back. Moreover, the local algorithm positioning was verified. Conclusion: The new image processing method for measuring ET from OCT images significantly reduces calculation time for this parameter, and avoids user intervention. The main advantages of this are that data can be analyzed more rapidly and reproducibly in clinical trials.