Forecasting and simulation of cutting force in virtual surgery based on particle filtering
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Forecasting and simulation of cutting force in virtual surgery based on particle filtering Qiangqiang Cheng1,2 · Pengyu Sun1,2 · Chunsheng Yang2 · Runqiao Yu1,2 · Peter Xiaoping Liu3 Accepted: 25 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract An accurate and realistic force feedback is very important in determining the realism of virtual surgery. In order to improve the accuracy of force simulation in cutting procedures, we proposed a novel method for forecasting and simulating the cutting force based on a particle filtering (PF) technique. Since the probability density function (PDF) is represented by particles, it is able to estimate accurately the interaction force between the surgical tool and soft tissue during cutting processes. The root mean square error (RMSE) of the PF-based method ranges from 0.0014 to 0.0034, and the mean absolute error (MAE) is less than 0.0399. Comparison of the experiment results with other methods demonstrated that the PF-based method can achieve a higher accuracy with different cutting speeds and angles. The application of the PF-based method to a virtual liver cutting procedure confirmed the effectiveness and accuracy of this method. Keywords Virtual surgery · Haptic interaction · Cutting force simulation · Artificial intelligence · Particle filtering
1 Introduction Virtual reality utilizes computer technologies to create a simulated environment so as to present users a sense of environmental immersion [1, 2]. As an important application of virtual reality, virtual surgery systems combined with the
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10489-020-01910-1) contains supplementary material, which is available to authorized users. Runqiao Yu
[email protected] Qiangqiang Cheng [email protected] Chunsheng Yang [email protected] Peter Xiaoping Liu [email protected] 1
Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition, Nanchang Hangkong University, Nanchang, China
2
National Research Council, Ottawa, Canada
3
Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada
medical information from actual surgery equipment, environment, and medical imaging (such as magnetic resonance imaging (MRI) and computer tomography (CT)) provide and simulate the process of surgical procedures [3–5]. As one of the most routine operations in surgery, the simulation of soft tissue cutting is an integral part of virtual surgery [6, 7]. Apart from visual presentation, haptic interaction is the most critical and difficult problem for cutting simulation. Although many soft tissues cutting models have been proposed to address this problem, there is still not a method which can simultaneously meet the requirements of computational speed and accuracy, due to the complex characteristics of soft tissue (such as anisotropy, inhomogeneous viscoelasticity, and approximate incompressibility) [8]. Furthermore, most of the traditional simulations
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