Tissue discrimination in anterior eye using three optical parameters obtained by polarization sensitive optical coherence tomography.

We developed a tissue discrimination algorithm of polarization sensitive optical coherence tomography (PS-OCT) based on the optical properties of tissues. We calculated the three-dimensional (3D) feature vector from the parameters intensity, extinction coefficient, birefringence, which were obtained by PS-OCT. The tissue type of each pixel was determined according to the position of the feature vector in the 3D feature space. The algorithm was applied for discriminating tissues of the human anterior eye segment. The conjunctiva, sclera, trabecular meshwork (TM), cornea, and uvea were well separated in the 3D feature space, and we observed them with good contrast. The TM line can be observed in the 3D discriminated volume, as observed by gonioscopy.We validated our method by applying our algorithm and histological data to porcine eyes. A marker was injected into sub-Tenon's space and the tissues that were anterior to the marker and posterior to the marker were successfully segmented by our algorithm.