OCT VOLUMETRIC DATA RESTORATION WITH LATENT DISTRIBUTION OF REFRACTIVE INDEX

This work proposes a novel restoration model for optical coherence tomography (OCT) data. The authors have been developing a multi-frequency swept (MS) en-face OCT device that can help understand the mechanism of the sensory epithelium in the cochlear. Although the device has merit in acquiring moving tissues, the broadened light gives a weak response; thus, some signal restorations are demanded. This work proposes the introduction of a formulation for OCT data restoration as a convex optimization problem by assuming a latent refractive index distribution. An algorithm to solve the problem with the primal-dual splitting (PDS) framework is then derived. The PDS has an advantage of requiring no inverse matrix operation and being able to handle high-dimensional data. The significance of the proposed model is verified by simulations on artificial data, followed by an experiment with the actual observation of 256 x 256 x 2000 voxels.