Segmentation of thin corrugated layers in high-resolution OCT images

Abstract

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 coe cient image with our matching layer attenuation coe cient segmentation (MLAS) algorithm. This algorithm repositions the initial segmentation such that it finds the point where the attenuation coe cient is close to the mean centerline attenuation. The algorithm does not utilize any sample specific prior knowledge in the attenuation coe cient 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 190 mm3 OCT volume of a thin corrugated varnish layer. Our technique can aid in the rapid characterization of layer stratigraphy and deepen our understanding of their condition.