Zhou M, Hao X, Eslami A, Huang K, Cai C, Lohmann CP, Navab N, Knoll A, Nasseri MA (2019)
Publication Type: Journal article
Publication year: 2019
Book Volume: 7
Pages Range: 63113-63122
Article Number: 8695065
DOI: 10.1109/ACCESS.2019.2912327
Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are 1) 3D needle point cloud segmentation in OCT volume and 2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method.
APA:
Zhou, M., Hao, X., Eslami, A., Huang, K., Cai, C., Lohmann, C.P.,... Nasseri, M.A. (2019). 6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery. IEEE Access, 7, 63113-63122. https://doi.org/10.1109/ACCESS.2019.2912327
MLA:
Zhou, Mingchuan, et al. "6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery." IEEE Access 7 (2019): 63113-63122.
BibTeX: Download