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Purpose: Emerging deep-brain stimulation (DBS) procedures require a high degree of accuracy in placement of neuroelectrodes, even in the presence of deformation due to cerebrospinal fluid (CSF) egress during surgical access. We are developing ventriculoscope and hand-eye calibration methods for a robot-assisted guidance system to augment accurate electrode placement through transventricular approach. Methods: The ventriculoscope camera was modelled and calibrated for lens distortion using three different checkerboards, followed by evaluation on a separate board. The experimental system employed a benchtop UR3e robot (Universal Robots, Denmark) and ventriculoscope (Karl Storz, Tuttlingen, Germany) affixed to the end effector – referred to as the robotassisted ventriculoscopy (RAV) platform. Performance was evaluated in terms of three error metrics (RPE, FCE and PDE). Experiments were conducted to estimate the camera frame of reference using hand-eye calibration methods, and evaluated using a ChAruco board, using five different solvers and residual calibration error as the metric. Results: Camera calibration demonstrated subpixel (0.81 ± 0.11) px reprojection error and projection distance error (PDE) <0.5 mm. The error was observed to converge for any checkerboard used given a sufficient number of calibration images. The hand-eye calibration exhibited sub-mm residual error (0.26 ± 0.18) mm insensitive to the solver used. Conclusions: The RAV system demonstrates sub-mm ventriculoscope camera calibration error and robot-to-camera handeye residual error, providing a valuable platform for the development of advanced 3D guidance systems for emerging DBS approaches. Future work aims to develop structure-from-motion (SfM) methods to reconstruct a 3D optical scene using endoscopic video frames and further testing using rigid and deformable anatomical phantoms as well as cadaver studies.
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