Top

Published in:

2022 | OriginalPaper | Chapter

A Review of Mass Spring Method Improvements for Modeling Soft Tissue Deformation

Authors : Mohd Nadzeri Omar, Yongmin Zhong

Published in: Human-Centered Technology for a Better Tomorrow

Publisher: Springer Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Significant research efforts have been dedicated to the creation of virtual reality simulators that empower medical students to learn anatomy and surgery in a virtual environment and allow surgeons to practice surgical operations. The degree of realism is determined by the simulation's accuracy and the processing efficiency of its underlying models. Deformable models should ideally be able to precisely recreate soft tissue deformation simultaneously providing real-time visual and force feedback. One of the most well-known approaches is the Finite Element Method (FEM). It has been demonstrated that the FEM can effectively replicate soft tissue deformation, but it requires a significant processing cost to enable real-time interaction. In this context, the Mass Spring Method (MSM) has been suggested as an alternative. The standard MSM model mimics soft tissue deformation with excellent computational performance but is constrained to linear behavior because it is based on simple Hooke's law theory. This paper provides recent studies on the enhancement of the standard MSM model to examine the viability of the MSM model to simulate soft tissue deformation for surgical simulation.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

previous chapter An Improved Momentum Rate in Artificial Neural Networks for Estimating Product Cycle Time at Semi-automatic Production

next chapter Injury Pattern Among Drivers Involved in Single Frontal Crash Based on the Police Reported Accident Data in Malaysia

Hsu WM, Hughes JF, Kaufman H (1992) Direct manipulation of free-form deformations. ACM SIGGRAPH Comput Graph 26:177–184CrossRef

MacCracken R, Joy KI (1996) Free-form deformations with lattices of arbitrary topology. In: Proceedings of the 23rd annual conference on computer graphics and interactive techniques—SIGGRAPH ’96, pp 181–188

Terzopoulos D, Platt J, Barr A, Fleischer K (1987) Elastically deformable models. ACM SIGGRAPH Comput Graph 21:205–214CrossRef

Ishikawa T, Sera H, Morishima S, Terzopoulos D (1998) Facial image reconstruction by estimated muscle parameter. In: Proceedings third IEEE international conference on automatic face and gesture recognition, pp 342–347

Gibson SF (1997) 3D chainmail. In: Proceedings of the 1997 symposium on interactive 3D graphics—SI3D ’97, pp 149–154

Klaus-Jürgen B (2014) Finite element procedures. Prentice-Hall, Englewood Cliffs, N.J

Bro-Nielsen M, Cotin S (1996) Real-time volumetric deformable models for surgery simulation using finite elements and condensation. Comput Graph Forum 15:57–66CrossRef

Taylor ZA, Cheng M, Ourselin S (2008) High-speed nonlinear finite element analysis for surgical simulation using graphics processing units. IEEE Trans Med Imaging 27:650–663CrossRef

Brebbia CA (1982) boundary element methods in engineering. Springer, Berlin (U.A.)

10.

Belytschko T, Krongauz Y, Organ D, Fleming M, Krysl P (1996) Meshless methods: an overview and recent developments. Comput Methods Appl Mech Eng 139:3–47CrossRef

11.

Xu S, Liu XP, Zhang H, Hu L (2011) A nonlinear viscoelastic tensor—mass visual model for surgery simulation. IEEE Trans Instrum Meas 60:14–20CrossRef

12.

Cooper L, Maddock S (1997) Preventing collapse within mass-spring-damper models of deformable objects. In: 5th international conference centre Europe, computer graphic visual, vol 2, no 1, pp 196–204

13.

Teschner M, Girod S, Girod B (2000) Direct computation of nonlinear soft-tissue deformation. Vis Model Vis 22–24

14.

Mohammadi H (2009) A numerical method to enhance the accuracy of mass-spring systems for modeling soft tissue deformations. J Appl Biomech 25:271–278CrossRef

15.

Pourhosseini M, Azimirad V, Kazemi M (2014) A new fast nonlinear modeling of soft tissue for surgical simulation. J Robot Surg 8:141–148CrossRef

16.

Duysak A, Zhang JJ, Ilankovan V (2003) Efficient modelling and simulation of soft tissue deformation using mass-spring systems. Int Congr Ser 1256:337–342CrossRef

17.

Luo Qi, Xiao J (2007) Contact and deformation modeling for interactive environments. IEEE Trans Rob 23:416–430CrossRef

18.

Cui T, Song A, Wu J (2008) Simulation of a mass-spring model for global deformation. Front Electr Electron Eng China 4:78–82CrossRef

19.

Sulaiman S, Sing Yee T, Bade A (2014) Effect of time complexities and variation of mass spring model parameters on surgical simulation. Malays J Fundam Appl Sci 9:171–179

20.

Chen F, Gu L, Huang P, Zhang J, Xu J (2007) Soft tissue modeling using nonlinear mass spring and simplified medial representation. In: 2007 29th annual international conference of the IEEE engineering in medicine and biology society, pp 5083–5086

21.

San-Vicente G, Aguinaga I, Celigueta JT (2012) Cubical mass-spring model design based on a tensile deformation test and nonlinear material model. IEEE Trans Visual Comput Graph 18:228–241CrossRef

22.

Shah R, Gupta A (2013) Non-linear cubic spring-mesh model for simulating biological tissues. Bio-Med Eng Sci 51(Supplement):U-12

23.

Garg A, Sreeni KG (2013) Haptic rendering of thin and soft objects. ICTACT J Image Video Process 3(3):539–550CrossRef

24.

Choi K-S, Sun H, Heng P-A (2004) An efficient and scalable deformable model for virtual reality-based medical applications. Artif Intell Med 32:51–69CrossRef

25.

Choi K-S, Sun H, Heng P-A (2003) Interactive deformation of soft tissues with haptic feedback for medical learning. IEEE Trans Inf Technol Biomed 7:358–363CrossRef

26.

Choi K-S, Sun H, Heng P-A, Zou J (2004) Deformable simulation using force propagation model with finite element optimization. Comput Graph 28:559–568CrossRef

27.

Mun P, Zhong Y, Shirinzadeh B, Smith J, Gu C (2011) An improved mass-spring model for soft tissue deformation with haptic feedback. ICMT 2011:1–6

28.

Chang Y-H, Chen Y-T, Chang C-W, Lin C-L (2010) Development scheme of haptic-based system for interactive deformable simulation. Comput Aided Des 42:414–424CrossRef

29.

Basafa E, Farahmand F, Vossoughi G (2008) A non-linear mass-spring model for more realistic and efficient simulation of soft tissues surgery. Stud Health Technol Inf 132(1):23–25

30.

Nikolaev S (2013) Non-linear mass-spring system for large soft tissue deformations modeling. Sci Tech J Inf Technol Mech Opt 5(87):88–94

31.

Keeve E, Girod S, Kikinis R, Girod B (1998) Deformable modeling of facial tissue for craniofacial surgery simulation. Comput Aided Surg 3:228–238CrossRef

32.

García M, Gómez M, Ruíz Ó, Boulanger P (2005) Spring–particle model for hyperelastic cloth. In: Canadian Congress of Applied Mechanics, CANCAM

33.

Hammer PE, del Nido PJ, Howe RD (2011) Anisotropic mass-spring method accurately simulates mitral valve closure from image-based models. Funct Imaging Model Heart 233–240

34.

Delingette H, Cotin S, Ayache N (1999) A hybrid elastic model allowing real-time cutting, deformations and force-feedback for surgery training and simulation. Proc Comput Animation 1999:70–81MATH

35.

Picinbono G, Delingette H, Ayache N (2003) Non-linear anisotropic elasticity for real-time surgery simulation. Graph Models 65:305–321CrossRef

36.

Liu XP, Xu S, Zhang H, Hu L (2011) A new hybrid soft tissue model for Visio-haptic simulation. IEEE Trans Instrum Meas 60:3570–3581CrossRef

37.

del-Castillo E, Basañez L, Gil E (2013) Modeling non-linear viscoelastic behavior under large deformations. Int J Non-Linear Mech 57:154–162

38.

Ahmadian MT, Nikooyan AA (2006) Modeling and prediction of soft tissue directional stiffness using in-vitro force-displacement data. Int J Sci Res 16:385–389

39.

Wang Y, Guo S (2014) Elasticity analysis of mass-spring model-based virtual reality vascular simulator. In: 2014 IEEE international conference on mechatronics and automation, pp 292–297

40.

Duan Y, Huang W, Chang H, Chen W, Zhou J, Teo SK, Su Y, Chui CK, Chang S (2016) Volume preserved mass-spring model with novel constraints for soft tissue deformation. IEEE J Biomed Health Inform 20:268–280CrossRef

41.

Maciel A, Boulic R, Thalmann D (2003) Deformable tissue parameterized by properties of real biological tissue. Surg Simul Soft Tissue Model 74–87

42.

Jansson J, Vergeest JSM (2002) A discrete mechanics model for deformable bodies. Comput Aided Des 34:913–928CrossRef

43.

Nogami R, Noborio H, Ujibe F, Fujii H (2004) Precise deformation of rheologic object under MSD models with many voxels and calibrating parameters. In: IEEE international conference on robotics and automation, 2004. Proceedings. ICRA ’04, pp 1919–1926

44.

Morris D, Salisbury K (2008) Automatic preparation, calibration, and simulation of deformable objects. Comput Methods Biomech Biomed Eng 11:263–279CrossRef

45.

Zerbato D, Galvan S, Fiorini P (2007) Calibration of mass spring models for organ simulations. In: 2007 IEEE/RSJ international conference on intelligent robots and systems, pp 370–375

46.

Sala A, Turini G, Ferrari M, Mosca F, Ferrari V (2011) Integration of biomechanical parameters in tetrahedral mass-spring models for virtual surgery simulation. In: 2011 annual international conference of the IEEE engineering in medicine and biology society, pp 4550–4554

47.

Baudet V, Beuve M, Jaillet F, Shariat B, Zara F (2009) Integrating tensile parameters in hexahedral mass-spring system for simulation. In: Proceeding of 29th international conference on computer graphics, visualization, and computer vision (WSCG ’09), pp 145–152

48.

Gelder AV (1998) Approximate simulation of elastic membranes by triangulated spring meshes. J Graph Tools 3:21–41CrossRef

49.

Lloyd B, Szekely G, Harders M (2007) Identification of spring parameters for deformable object simulation. IEEE Trans Visual Comput Graph 13:1081–1094CrossRef

50.

Delingette H (2008) Triangular springs for modeling nonlinear membranes. IEEE Trans Visual Comput Graph 14:329–341CrossRef

51.

Deussen O, Kobbelt L, Tücke P (1995) Using simulated annealing to obtain good nodal approximations of deformable bodies. Eurographics 30–43

52.

Louchet J, Provot X, Crochemore D (1995) Evolutionary identification of cloth animation models. Eurographics 44–54

53.

Joukhadar A, Garat F, Laugier C (1997) Parameter identification for dynamic simulation. Proc Int Conf Robot Autom 1928–1933

54.

Etzmuss O, Gross J, Strasser W (2003) Deriving a particle system from continuum mechanics for the animation of deformable objects. IEEE Trans Visual Comput Graph 9:538–550CrossRef

55.

Bianchi G, Solenthaler B, Székely G, Harders M (2004) Simultaneous topology and stiffness identification for mass-spring models based on FEM reference deformations. Med Image Comput Comput-Assist Interv MICCAI 2004, pp 293–301

56.

Mosegaard J (2003) Parameter optimisation for the behaviour of elastic models over time. Stud Health Technol Inform 98:253–255

57.

Qiao B, Chen G, Ye X (2009) The research of soft tissue deformation based on mass-spring model. In: 2009 international conference on mechatronics and automation, pp 4655–4660

58.

Zhu L, Ye X, Ji’er X, Gu Y, Guo S (2010) A real-time deformation modeling scheme of soft tissue for virtual surgical. In: 2010 ieee international conference on information and automation, pp 771–775

59.

Georgii J, Westermann R (2005) Mass-spring systems on the GPU. Simul Model Pract Theor 13:693–702CrossRef

60.

Leon CA, Eliuk S, Gomez HT (2010) Simulating soft tissues using a GPU approach of the mass-spring model. 2010 IEEE Virtual Reality Conf (VR) 261–262

61.

Vassilev T, Rousev R (2008) Algorithm and data structures for implementing a mass-spring deformable model on GPU. Res Lab Univ Ruse, pp 102–109

62.

Rasmusson A, Mosegaard J, S∅rensen TS. Exploring parallel algorithms for volumetric mass-spring-damper models in CUDA. Biomed Simul 49–58

63.

Etheredge CE (2011) A parallel mass-spring model for soft tissue simulation with haptic rendering in CUDA. In: 15th Twente student conference on IT

64.

Fung YC (2011) Biomechanics: mechanical properties of living tissues. Springer, New York

65.

Holzapfel GA (2001) Biomechanics of soft tissue. Handbook Mater Behav Models 3:1049–1063

Title: A Review of Mass Spring Method Improvements for Modeling Soft Tissue Deformation
Authors: Mohd Nadzeri Omar
Yongmin Zhong
Publisher: Springer Singapore
Book: Human-Centered Technology for a Better Tomorrow
Print ISBN: 978-981-16-4114-5

Electronic ISBN: 978-981-16-4115-2

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-981-16-4115-2_16