Intraocular Reflection Modeling and Avoidance Planning in Image-Guided Ophthalmic Surgeries

Abstract

Intuitive enhancement of surgical precision in robotic retinal surgery highly depends on the stable acquisition of intraocular imaging data. Such acquisition requires segmenting intraocular components, especially instrument-tip positions, to achieve state estimation and subsequent navigation and motion control. However, intraocular light reflections and glares significantly impact instrument segmentation, state estimation, and subsequent visual servoing in retinal surgery. At the same time, light reflections are among the sources of information for intraoperative navigation. In this work, we propose a method for modeling and optimizing light reflections using microscopy as the standard surgical imaging modality. Beyond optimization, our approach seamlessly integrates the optimized reflection with path planning, strategically circumventing reflection areas and ensuring uninterrupted visibility of instrument tips throughout the surgical procedure. Experiments demonstrate the methodology’s efficacy in avoiding glare affections during eye surgeries.