This paper presents techniques for robot-aided intraocular surgery using monocular vision in order to overcome erroneous stereo reconstruction in an intact eye. We propose a new retinal surface estimation method based on a structured-light approach. A handheld robot known as the Micron enables automatic scanning of a laser probe, creating projected beam patterns on the retinal surface. Geometric analysis of the patterns then allows planar reconstruction of the surface. To realize automated surgery in an intact eye, monocular hybrid visual servoing is accomplished through a scheme that incorporates surface reconstruction and partitioned visual servoing. We investigate the sensitivity of the estimation method according to relevant parameters and also evaluate its performance in both dry and wet conditions. The approach is validated through experiments for automated laser photocoagulation in a realistic eye phantom in vitro. Finally, we present the first demonstration of automated intraocular laser surgery in porcine eyes ex vivo.
Keyphrases
- minimally invasive
- coronary artery bypass
- deep learning
- machine learning
- optical coherence tomography
- diabetic retinopathy
- high throughput
- surgical site infection
- high resolution
- high speed
- magnetic resonance
- electron microscopy
- computed tomography
- percutaneous coronary intervention
- coronary artery disease
- single molecule
- dual energy