EyeSLAM: Real‐time simultaneous localization and mapping of retinal vessels during intraocular microsurgery

Abstract

BACKGROUND: Fast and accurate mapping and localization of the retinal vasculature is critical to increasing the effectiveness and clinical utility of robot-assisted intraocular microsurgery such as laser photocoagulation and retinal vessel cannulation. METHODS: The proposed EyeSLAM algorithm delivers 30 Hz real-time simultaneous localization and mapping of the human retina and vasculature during intraocular surgery, combining fast vessel detection with 2D scan-matching techniques to build and localize a probabilistic map of the vasculature. RESULTS: In the harsh imaging environment of retinal surgery with high magnification, quick shaky motions, textureless retina background, variable lighting and tool occlusion, EyeSLAM can map 75% of the vessels within two seconds of initialization and localize the retina in real time with a root mean squared (RMS) error of under 5.0 pixels (translation) and 1° (rotation). CONCLUSIONS: EyeSLAM robustly provides retinal maps and registration that enable intelligent surgical micromanipulators to aid surgeons in simulated retinal vessel tracing and photocoagulation tasks.