@inproceedings{dd49caecfa9142528a9b3a652872f2e6,
title = "Robot-assisted ventriculoscopic 3D reconstruction for guidance of deep-brain stimulation surgery",
abstract = "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. ",
keywords = "Augmented reality, Computer Vision, Image-guided surgery, Neurosurgery, Ventriculoscopy",
author = "P. Vagdargi and Ali Uneri and Jones, {C. K.} and P. Wu and R. Han and M. Luciano and Anderson, {W. S.} and Hager, {G. D.} and Siewerdsen, {J. H.}",
note = "Funding Information: This work is supported by NIH grant U01-NS-107133 and Biomedical Research Partnership (BRP) with Medtronic, PLC. The authors extend their thanks to Dr. Patrick Helm from Medtronic for constructive conversations and collaboration. Publisher Copyright: {\textcopyright} 2021 SPIE.; Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling ; Conference date: 15-02-2021 Through 19-02-2021",
year = "2021",
doi = "10.1117/12.2582173",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Linte, {Cristian A.} and Siewerdsen, {Jeffrey H.}",
booktitle = "Medical Imaging 2021",
}