AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Complex System Modeling and Simulation Article
PDF (8.7 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Real-Time Laparoscopic Cholecystectomy Simulation Using a Particle-Based Physical System

Hongyu Wu1,2, Fan Ye1,2, Yang Gao1,2, Yu Cong3, Aimin Hao1,2( )
State Key Laboratory of Virtual Reality Technology and Systems, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100191, China
Research Unit of Virtual Human and Virtual Surgery(2019RU004), Chinese Academy of Medical Sciences, Beijing 100730, China.
Beijing UniDraw Virtual Reality Technology Research Institute Co., Ltd, Beijing 101300, China
Show Author Information

Abstract

Laparoscopic cholecystectomy is used to treat cholecystitis and cholelithiasis. Because the high risk of the surgery prevents novice doctors from practicing it on real patients, VR-based surgical simulation has been developed to simulate surgical procedures to train surgeons without patients, cadavers, or animals. In this study, we propose a real-time system designed to provide plausible visual and tactile simulation of the main surgical procedures. To achieve this, the physical properties of organs are modeled by particles, and cluster-based shape matching is used to simulate soft deformation. The haptic interaction between tools and soft tissue is modeled as a collision between a capsule and particles. Constraint-based haptic rendering is used to generate feedback force and the non-penetrating position of the virtual tool. The proposed system can simulate the major steps of laparoscopic cholecystectomy, such as the anatomy of Calot’s triangle, clipping of the cystic duct and biliary artery, disjunction of the cystic duct and biliary artery, and separation of the gallbladder bed. The experimental results show that haptic rendering can be performed at a high frequency (> 900 Hz), whereas mesh skinning and graphics rendering can be performed at 60 frames per second (fps).

Keywords

virtual surgerylaparoscopic cholecystectomyposition-based dynamics

References

1

M. Müller, B. Heidelberger, M. Teschner, and M. H. Gross, Meshless deformations based on shape matching, ACM Trans. Graph., vol. 24, no. 3, pp. 471–478, 2005.
Crossref Google Scholar
2

M. Macklin, M. Müller, N. Chentanez, and T. Kim, Unified particle physics for real-time applications, ACM Trans. Graph., vol. 33, no. 4, p. 153, 2014.
Crossref Google Scholar
3
H. Wang, Y. Ding, Q. Yang, and H. Pu, Cloth simulation algorithm based on the mass-spring model and the non-planar vortex lattice model, in Proc. 2019 International Conference on Frontier Computing, Kyushu, Japan, 2019, pp. 578–585.https://doi.org/10.1007/978-981-15-3250-4_72
Crossref
4

H. Courtecuisse, J. Allard, P. Kerfriden, S. P. A. Bordas, S. Cotin, and C. Duriez, Real-time simulation of contact and cutting of heterogeneous soft-tissues, Medical Image Analysis, vol. 18, no. 2, pp. 394–410, 2014.
Crossref Google Scholar
5

M. Müller, B. Heidelberger, M. Hennix, and J. Ratcliff, Position based dynamics, J. Vis. Commun. Image R., vol. 18, no. 2, pp. 109–118, 2007.
Crossref Google Scholar
6

S. Bouaziz, S. Martin, T. T. Liu, L. Kavan, and M. Pauly, Projective dynamics: Fusing constraint projections for fast simulation, ACM Trans. Graph., vol. 33, no. 4, p. 154, 2014.
Crossref Google Scholar
7

M. H. Kee, K. Um, W. Jeong, and J. Han, Constrained projective dynamics: Real-time simulation of deformable objects with energy-momentum conservation, ACM Trancs. Graph., vol. 40, no. 4, pp. 1–12, 2021.
Crossref Google Scholar
8
S. Yoon, B. Salomon, M. Lin, and D. Manocha, Fast collision detection between massive models using dynamic simplification, in Proc. 2004 Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, Nice, France, 2004, pp. 136–146.https://doi.org/10.1145/1057432.1057450
Crossref
9

G. Young and A. Krishnamurthy, GPU-accelerated generation and rendering of multi-level voxel representations of solid models, Comput. Graph., vol. 75, pp. 11–24, 2018.
Crossref Google Scholar
10
W. A. McNeely, K. D. Puterbaugh, and J. J. Troy, Advances in voxel-based 6-DOF haptic rendering, in Proc. ACM SIGGRAPH 2005 Courses, Los Angeles, CA, USA, 2005, pp. 50–71.https://doi.org/10.1145/1198555.1198606
Crossref
11

D. Wang, X. Zhang, Y. Zhang, and J. Xiao, Configuration-based optimization for six degree-of-freedom haptic rendering for fine manipulation, IEEE Trans. Haptics., vol. 6, no. 2, pp. 167–180, 2012.
Crossref Google Scholar
12

D. Wang, Y. Shi, S. Liu, Y. Zhang, and J. Xiao, Haptic simulation of organ deformation and hybrid contacts in dental operations, IEEE Trans. Haptics., vol. 7, no. 1, pp. 48–60, 2014.
Crossref Google Scholar
13

G. Yu, D. Wang, Y. Zhang, and J. Xiao, Simulating sharp geometric features in six degrees-of-freedom haptic rendering, IEEE Trans. Haptics., vol. 8, no. 1, pp. 67–78, 2014.
Crossref Google Scholar
14

S. Li, Q. Xia, A. Hao, H. Qin, and Q. Zhao, Haptics-equiped interactive PCI simulation for patient-specific surgery training and rehearsing, Sci. China Inf. Sci., vol. 59, no. 10, p. 103101, 2016.
Crossref Google Scholar
15

G. S. Ruthenbeck, J. Hobson, A. S. Carney, S. Sloan, R. Sacks, and K. J. Reynolds, Toward photorealism in endoscopic sinus surgery simulation, Am. J. Rhinol. Allergy., vol. 27, no. 2, pp. 138–143, 2013.
Crossref Google Scholar
16

J. I. Fann, M. E. Sullivan, K. M. Skeff, G. A. Stratos, J. D. Walker, E. A. Grossi, E. D. Verrier, G. L. Hicks, and R. H. Feins, Teaching behaviors in the cardiac surgery simulation environment, J. Thorac. Cardiovasc. Surg., vol. 145, no. 1, pp. 45–53, 2013.
Crossref Google Scholar
17

D. Wang, Y. Zhang, J. Hou, Y. Wang, P. Lv, Y. Chen, and H. Zhao, IDental: A haptic-based dental simulator and its preliminary user evaluation, IEEE Trans. Haptics., vol. 5, no. 4, pp. 332–343, 2011.
Crossref Google Scholar
18

Y. Kim, L. Kim, D. Lee, S. Shin, H. Cho, F. Roy, and S. Park, Deformable mesh simulation for virtual laparoscopic cholecystectomy training, Vis. Comput., vol. 31, no. 4, pp. 485–495, 2015.
Crossref Google Scholar
19

Y. Sui, J. Pan, H. Qin, H. Liu, and Y. Lu, Real-time simulation of soft tissue deformation and electrocautery procedures in laparoscopic rectal cancer radical surgery, Int. J. Med. Robot., vol. 13, no. 4, p. e1827, 2017.
Crossref Google Scholar
20

M. Yiasemidou, D. Glassman, P. Vasas, S. Badiani, and B. P. Patel, Faster simulated laparoscopic cholecystectomy with haptic feedback technology, Open Access Surgery, vol. 4, pp. 39–44, 2011.
Crossref Google Scholar
21
F. G. Hamaz-Lup, A. Seitan, D. M. Popovici, and C. M. Bogdan, Liver pathology simulation: Algorithm for haptic rendering and force maps for palpation assessment, arXiv preprint arXiv: 1903.01249, 2019.
22
J. Pan, L. Zhang, P. Yu, Y. Shen, H. Wang, H. Hao, and H. Qin, Real-time VR simulation of laparoscopic cholecystectomy based on parallel position-based dynamics in GPU, in Proc. 2020 IEEE Conference on Virtual Reality and 3D User Interfaces, Atlanta, GA, USA, 2020, pp. 548–556.https://doi.org/10.1109/VR46266.2020.00076
Crossref
23

D. Goldfarb and A. Idnani, A numerically stable dual method for solving strictly convex quadratic programs, ACM Trans. Graph., vol. 27, no. 1, pp. 1–33, 1983.
Crossref Google Scholar
24

Z. Chen and H. Zhang, Neural marching cubes, ACM Trans. Graph., vol. 40, no. 6, p. 251, 2021.
Crossref Google Scholar
25

L. Kavan, S. Collins, J. Žára, and C. O’Sullivan, Geometric skinning with approximate dual quaternion blending, ACM Trans. Graph., vol. 27, no. 4, pp. 1–23, 2008.
Crossref Google Scholar
26
3D Systems, https://www.3dsystems.com/hapticsdevices/touch/specifications, 2022.
27

W. Gong, Z. Liao, X. Mi, L. Wang, and Y. Guo, Nonlinear equations solving with intelligent optimization algorithms: A survey, Complex System Modeling and Simulation, vol. 1, no. 1, pp. 15–32, 2021.
Crossref Google Scholar
28

Z. Cui, L. Zhao, Y. Zeng, Y. Ren, W. Zhang, and X. Gao, Novel PIO algorithm with multiple selection strategies for many-objective optimization problems, Complex System Modeling and Simulation, vol. 1, no. 4, pp. 291–307, 2021.
Crossref Google Scholar
Complex System Modeling and Simulation
Volume 2 Issue 2,
June 2022
Pages 186-196
DOI: 10.23919/CSMS.2022.0009
Cite this article:
Wu H, Ye F, Gao Y, et al. Real-Time Laparoscopic Cholecystectomy Simulation Using a Particle-Based Physical System. Complex System Modeling and Simulation, 2022, 2(2): 186-196. https://doi.org/10.23919/CSMS.2022.0009

1261

Views

161

Downloads

1

Crossref

1

Scopus

Altmetrics
Received: 01 July 2021
Revised: 18 April 2022
Accepted: 14 June 2022
Published: 30 June 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Return