Title: Vascular centreline extraction for virtual reality interventional training systems

Authors: Peng Shi; Shuxiang Guo; Xiaoliang Jin

Addresses: Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, The Ministry of Industry and Information Technology, Beijing Institute of Technology, Haidian District, Beijing, 100081, China; Graduate School of Engineering, Kagawa University, Hayashi-cho, Takamatsu, 761-0396, Japan ' Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, The Ministry of Industry and Information Technology, Beijing Institute of Technology, Haidian District, Beijing, 100081, China; Graduate School of Engineering, Kagawa University, Hayashi-cho, Takamatsu, 761-0396, Japan ' Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, The Ministry of Industry and Information Technology, Beijing Institute of Technology, Haidian District, Beijing, 100081, China; Graduate School of Engineering, Kagawa University, Hayashi-cho, Takamatsu, 761-0396, Japan

Abstract: Vascular interventional surgery requires surgeon to be highly skilled at manipulating the surgical tools to avoid damaging blood vessel. Virtual reality (VR) interventional training systems were developed to reduce the training cost and improve training. For virtual interventional radiology, centreline of the vasculature is often used to reconstruct vasculature and detect the contact between surgical tools and blood vessel wall. In this paper, we introduce a centreline extraction method which is suitable for the vasculature mesh. The extraction method assume that the vasculature mesh is a set of continuous cylindrical shapes. The centreline is formed by centre point of the cylindrical shapes, and the centreline is satisfied rotational symmetry. In addition, we propose a pre-processing strategy to convert the mesh representation to point cloud representation. This strategy can merge duplicate vertex and normal vector for vasculature mesh while preserving the integrity of the vasculature. The performance of our method is experimentally validated.

Keywords: centreline extraction; rotational symmetry axis; vasculature mesh; virtual interventional radiology; VR interventional training system.

DOI: 10.1504/IJMA.2022.130400

International Journal of Mechatronics and Automation, 2022 Vol.9 No.4, pp.172 - 179

Received: 19 Oct 2021
Accepted: 21 Apr 2022
Published online: 19 Apr 2023 *

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