Abstract
Optical coherence tomography (OCT) is a preferred imaging technology in ophthalmology for diagnosis and management of eye disease. Standard-of-care clinical OCT systems require patients to sit upright, brace their head against the instrument, and fix their gaze into its sensing aperture. These limitations exclude those with involuntary head and eye movements, such as those present in Parkinson's disease and nystagmus, respectively, from undergoing OCT imaging. To overcome these restrictions, we combine our robotic OCT paradigm, which allows flexible patient positioning during imaging, with active cancellation of periodic motion to reduce image artifact during acquisition. We accomplish this by measuring eye motion with on-board pupil cameras, fitting the movement profile in real-time, and augmenting OCT scan waveforms using the predicted eye position. We evaluate this predictive imaging scheme with eye phantoms to precisely simulate motions typical of head and eye movement disorders and compare it to real-time scan aiming. Using registration shift in captured OCT images to quantify residual motion artifact, we demonstrate motion reduction by up to 98.5 % for typical nystagmus frequencies and an average 3.4 × reduction in residual motion compared to scan aiming alone. This approach may provide access to accurate OCT imaging for those with involuntary eye and head movement.