Open Access

ARTICLE

A Fast and Accurate Vascular Tissue Simulation Model Based on Point Primitive Method

Xiaorui Zhang^1,2,*, Hailun Wu¹, Wei Sun¹, Aiguo Song³, Sunil Kumar Jha⁴

1 Jiangsu Engineering Center of Network Monitoring, Engineering Research Center of Digital Forensics, Ministry of Education, School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, 210044, China
2 Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
3 State Key Laboratory of Bioelectronics, Jiangsu Key Lab of Remote Measurement and Control, School of Instrument Science and Engineering, Southeast University, Nanjing, 210096, China
4 Faculty of Information Technology, University of Information Technology and Management in Rzeszow, Rzeszow, 35-225, Poland

* Corresponding Author: Xiaorui Zhang. Email:

Intelligent Automation & Soft Computing 2021, 27(3), 873-889. https://doi.org/10.32604/iasc.2021.013541

Received 30 August 2020; Accepted 14 February 2021; Issue published 01 March 2021

Abstract

Virtual surgery simulation is indispensable for virtual vascular interventional training system, which provides the doctor with visual scene between catheter and vascular. Soft tissue deformation, as the most significant part, determines the success or failure of the virtual surgery simulation. However, most soft tissue deformation model cannot simultaneously meet the requirement of high deformation accuracy and real-time interaction. To solve the challenge mentioned above, this paper proposes a fast and accurate vascular tissue simulation model based on point primitive method. Firstly, the proposed model simulates a deformation of the internal structure of the vascular tissue by adopting a point primitive method. Besides, the stretching constraint and elastic potential energy constraint are introduced to control and correct node motion. Furthermore, a mapping function from the interior to the surface of the vascular tissue is constructed based on moving least squares algorithm to render the visual effect of deformation. Finally, a training system based on the proposed model is set up on the PHANTOM OMNI force-tactile feedback device to realize the deformation simulation of the virtual vascular tissue. Experimental results shows that the proposed model can enhance real-time performance of the training system under the premise of ensuring deformation accuracy, as well as simulate the elasticity of soft tissue.

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Keywords

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