EyeSAM: graph-based localization and mapping of retinal vasculature during intraocular microsurgery.

PURPOSE: Robot-assisted intraocular microsurgery can improve performance by aiding the surgeon in operating on delicate micron-scale anatomical structures of the eye. In order to account for the eyeball motion that is typical in intraocular surgery, there is a need for fast and accurate algorithms that map the retinal vasculature and localize the retina with respect to the microscope. METHODS: This work extends our previous work by a graph-based SLAM formulation using a sparse incremental smoothing and mapping (iSAM) algorithm. RESULTS: The resulting technique, "EyeSAM," performs SLAM for intraoperative vitreoretinal surgical use while avoiding spurious duplication of structures as with the previous simpler technique. The technique also yields reduction in average pixel error in the camera motion estimation. CONCLUSIONS: This work provides techniques to improve intraoperative tracking of retinal vasculature by handling loop closures and achieving increased robustness to quick shaky motions and drift due to uncertainties in the motion estimation.

Toward Monocular Camera-Guided Retinal Vein Cannulation with an Actively Stabilized Handheld Robot.

In this paper we describe work towards retinal vessel cannulation using an actively stabilized handheld robot, guided by monocular vision. We employ a previously developed monocular camera based surface reconstruction method using automated laser beam scanning over the retina. We use the reconstructed plane to find a coordinate transform between the 2D image plane coordinate system and the global 3D frame. Within a hemispherical region around the target, we use motion scaling for higher precision. The contribution of this work is the homography matrix estimation using monocular vision and application of the previously developed laser surface reconstruction to Micron guided vein cannulation. Experiments are conducted in a wet eye phantom to show the higher accuracy of the surface reconstruction as compared to standard stereo reconstruction. Further, experiments to show the increased surgical accuracy due to motion scaling are also carried out.

Electromagnetic Tracker for Active Handheld Robotic Systems.

We describe the development of the In-Loop Electromagnetic Tracker (ILEMT), designed to meet the demanding latency and resolution requirements for active stabilization of hand motion during precision manipulations such as microsurgery. The prototype surpasses the fastest commercial EM trackers by > 4× in root bandwidth/resolution and 2× in latency. The use of two widely spaced carrier frequencies (e.g., 300 Hz and 10 kHz) enables a particularly simple way of reducing the eddy-current interference caused by nonferrous metals present in the workspace. Previously, metal compatibility has only been achieved at a large cost to measurement speed.