Optical coherence tomography (OCT) is a noninvasive diagnostic method that
offers a view into the superficial layers of the skin in vivo in real-time. OCT
delivers morphological images of microstructures within the skin. Epidermal
thickness in OCT images is of paramount importance, since dermo-epidermal
junction (DEJ) location alteration is the start of several skin abnormalities. Due to
the presence of speckle noise, devising an algorithm for locating DEJ in the OCT
images is challenging. In this study we propose a semi-automatic DEJ detection
algorithm based on graph theory that is resistant to speckle. In this novel approach
we use attenuation map as a complementary feature compared to the previous
methods that are mainly based on the intensity information. The method is based
on converting border segmentation problem to the shortest path problem using
graph theory. To smooth borders, we introduced a thinning fuzzy system enabling
closer match to manual segmentation. Subsequently, an averaged A-scan analysis
is performed to obtain the mean epidermal thickness. The DEJ detection method is
performed on 96 B-Scan OCT skin images taken from different sites of body of
healthy individuals. The results are evaluated based on several expert’s visual
analysis.
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