Speckle Modelization in OCT Images for Skin Layers Segmentation

In dermatology, the optical coherence tomography (OCT) is used to visualize the skin over a few millimetre depth. These images are affected by speckle, which can alter the interpretation, but which also carry information that characterizes locally the visualized tissue. In this paper, we present a statistical study of the speckle distribution in OCT images. The capability of three probability density functions (pdf) (Rayleigh, Lognormal, and Nakagami) to differentiate the speckle distribution according to the skin layer is analysed. For each pdf, the vector of parameters, estimated over several images which are annotated by experts, are mapped onto a parameter space. Quantitative results over 30 images are compared to the manual delineations of 5 experts. Results confirm the potential of the method for the segmentation of the layers of the skin.