Tracking the optic nerve head in OCT video using dual eigenspaces and an adaptive vascular distribution model

Optical coherence tomography (OCT) is a novel ophthalmic imaging modality generating cross sectional views of the retina. OCT systems form images in 1.5 seconds by directing a superluminescent diode (SLD) beam over the retinal surface. Involuntary ocular motion may occur, however, causing incorrect locations to be imaged. This motion may leave no obvious artifacts and thus go undetected. For glaucoma monitoring especially, knowing the measurement location is crucial. The commercially available OCT system displays a near-IR video of the SLD beam traversing the retinal around the optic nerve head. We developed a prototype system to detect the nerve head and SLD beam position in this video, and report the actual scan path relative to the nerve head. This system must cope with low image contrast and few reliable retinal features. In its adaptive model generation phase, the system directly detects vasculature and the nerve head and builds an individual model of the vascular pattern. The nerve head identification is multi-tiered, using a novel, dual-eigenspace technique and a geometric comparison of detected vessel positions and nerve head hypotheses. In its operational phase, a correspondence is achieved between detected vasculature and the model. The system was evaluated on video of three subjects not used to form the eigenspaces. The system located the optic nerve head to within 5 pixels in 99% of 2800 video fields manually inspected, and was thus able to determine the true scan path relative to the nerve head.