Segmentation of thin corrugated layers in high-resolution OCT images

In this paper we present a novel method for the segmentation of thin corrugated layers in high resolution optical coherence tomography (OCT) images. First, we make an initial segmentation, for example with graph based segmentation that, for highly corrugated interfaces, leads to many segmentation errors. Second, we resegment the initial outcome, based on the OCT attenuation coefficient image with our matching layer attenuation coefficient segmentation (MLAS) algorithm. This algorithm repositions the initial segmentation such that it finds the point where the attenuation coefficient is close to the mean centerline attenuation. The algorithm does not utilize any sample specific prior knowledge in the attenuation coefficient based segmentation step. For simulated and measured data of strongly corrugated samples, such as is the case for varnish layers on paintings and furniture, the MLAS algorithm performs much better than the conventional segmentation. Finally, we show 3D segmentation of an entire 190 mm3 OCT volume. Our technique can aid in the rapid characterization of layer stratigraphy and deepen our understanding of their condition.