Multimedia Tools and Applications

, Volume 73, Issue 3, pp 1795–1817 | Cite as

A visualization tool of 3-D time-varying data for the simulation of tissue growth

  • Belgacem Ben YoussefEmail author


Data Visualization affords us the ability to explore the spatial and temporal domains of many time-varying phenomena. In this article, we describe our application of visualization to a three-dimensional simulation model for tissue growth. We review the different components of the model where cellular automata is used to model populations of cells that execute persistent random walks, collide, and proliferate until they reach confluence. We then describe the system architecture of the developed visualization tool, the employed rendering techniques, and the related prototyping interfaces. We also discuss some of the visualization results obtained thus far that are pertinent to enhancing the validity of the computational model. This visualization tool could be useful in facilitating the research of scientists by providing them with meaningful means to interpret and analyze simulation data and to compare them to experimental results. Our objective in this work is to develop computer-aided design solutions that support the simulation of tissue growth and its design exploration.


Visualization Tissue growth Time-varying data 3-D simulation model Cellular automata 



The author would like to acknowledge the support for this research provided by the Research Centre in the College of Computer & Information Sciences (under project number: RC120920) and the Deanship of Scientific Research, both at King Saud University. Early contribution to this work from Haris Widjaya is also acknowledged. Finally, comments received from the anonymous reviewers are acknowledged for helping to improve this article.


  1. 1.
    Ben Youssef B (2004) Simulation of cell population dynamics using 3-D cellular automata. In Proceedings of the Sixth International Conference on Cellular Automata for Research and Industry (ACRI 2004), Lecture Notes of Computer Science (LNCS) vol. 3305, 562–571, Springer-VerlagGoogle Scholar
  2. 2.
    Ben Youssef B, Tang L (2010) Simulation of multiple cell population dynamics using a 3-D cellular automata model for tissue growth. Int J Nat Comput Res 1:1–18CrossRefGoogle Scholar
  3. 3.
    Ben Youssef B, Widjaya H (2005) An early look at the visualization of three-dimensional tissue growth. In Proceedings of the Seventh IEEE International Symposium on Multimedia (IEEE ISM2005), Irvine, CA, December 12–14, 128–135Google Scholar
  4. 4.
    Biddiscombe J, Soumagne J, Oger G, Guibert D, Piccinali J-G (2012) Parallel computational steering for HPC applications using HDF5 files in distributed shared memory. IEEE T Vis Comput Gr 18(6):852–864CrossRefGoogle Scholar
  5. 5.
    Bratley P, Fox BL, Schrage, LE (1987) A guide to simulation, 2nd edn. Springer-VerlagGoogle Scholar
  6. 6.
    Burgess BT, Myles JL, Dickinson RB (2000) Quantitative analysis of adhesion-mediated cell migration in three-dimensional gels of RGD-grafted collagen. Ann Biomed Eng 28:110–118CrossRefGoogle Scholar
  7. 7.
    Cheng G, Ben Youssef B, Markenscoff P, Zygourakis K (2006) Cell population dynamics modulate the rates of tissue growth processes. Biophys J 90:713–724CrossRefGoogle Scholar
  8. 8.
    Childs H, Brugger E, Bonnell K, Meredith J, Miller M, Whitlock B, Max, NA (2005) Contract based system for large data visualization. In Proceedings of the IEEE Conference on Visualization (IEEE VIS 05), 191–198Google Scholar
  9. 9.
    Deussen O, Hanrahan P, Lintermann B, Měch R, Pharr M, Prusinkiewicz P (1998) Realistic modeling and rendering of plant ecosystems. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’98), 275–286Google Scholar
  10. 10.
    Earnshaw RA, Wiseman N (1992) An introductory guide to scientific visualization. Springer-VerlagGoogle Scholar
  11. 11.
    Ellsworth D, Chiang L-J, Shen H-W (2000) Accelerating time-varying hardware volume rendering using TSP trees and color-based error metrics. In Proceedings of the IEEE symposium on volume visualization, 119–128Google Scholar
  12. 12.
    Engel K, Kraus M, Ertl T (2001) High-quality pre-integrated volume rendering using hardware-accelerated pixel shading. In Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Workshop on Graphics Hardware, 9–16Google Scholar
  13. 13.
    Fishwick PA (1995) Simulation model design and execution: Building digital worlds. Prentice Hall, Inc., Englewood CliffsGoogle Scholar
  14. 14.
    Gail MH, Boone CW (1970) The locomotion of mouse fibroblasts is tissue culture. Biophys J 10(10):980–993CrossRefGoogle Scholar
  15. 15.
    Gruler H, Bultmann BD (1988) Analysis of cell movement. Blood Cells 10(1):61–77Google Scholar
  16. 16.
    Hagedorn J, Dunkers J, Peskin A, Kelso J, Terrill JD (2006) Quantitative, interactive measurement of tissue engineering scaffold structure in an immersive visualization environment. Biomater Forum 28:6–9Google Scholar
  17. 17.
    Hagedorn JG, Dunkers JP, Satterfield SG, Peskin AP, Kelso JT, Terrill JE (2007) Measurement tools for the immersive visualization environment: steps toward the virtual laboratory. J Res Nat Inst Stand Technol 112:257–270CrossRefGoogle Scholar
  18. 18.
    Johnson CR, Parker SG, Hansen C, Kindlmann GL, Livnat Y (1999) Interactive simulation and visualization. IEEE Comput 32(12):59–65CrossRefGoogle Scholar
  19. 19.
    Johnson CR, Weinstein DM (2006) Biomedical computing and visualization. In Proceedings of the 29th Australasian computer science conference (ACSC 2006), Hobart, Australia, 3–10Google Scholar
  20. 20.
    Kitware Inc. (2010) The VTK user’s guide. Kitware, IncGoogle Scholar
  21. 21.
    Komura D, Nakamura H, Tsutsumi S, Aburatani H, Ihara S (2004) Multidimensional support vector machines for visualization of gene expression data. In Proceedings of the 2004 ACM Symposium on Applied Computing (ACM SAC’04), 175–179Google Scholar
  22. 22.
    Lacroute P, Levoy M (1994) Fast volume rendering using a shear-warp factorization of the viewing transformation. In Proceedings of the 21st annual conference on computer graphics and interactive techniques (SIGGRAPH’94), 451–458Google Scholar
  23. 23.
    Langer R, Vacanti J (1993) Tissue engineering. Science 260:920–926CrossRefGoogle Scholar
  24. 24.
    Lauffenburger DA, Linderman JJ (1993) Receptors: Models for binding trafficking and signaling. Oxford University Press, New YorkGoogle Scholar
  25. 25.
    Law AM (2007) Simulation modeling & analysis, 3rd edn. McGraw-Hill, Inc., BostonGoogle Scholar
  26. 26.
    Lee Y, Markenscoff P, McIntire LV, Zygourakis K (1995) Characterization of endothelial cell locomotion using a Markov chain model. Biochem Cell Biol 73:461–472CrossRefGoogle Scholar
  27. 27.
    Lee Y, McIntire LV, Zygourakis K (1994) Analysis of endothelial cell locomotion: differential effects of motility and contact inhibition. Biotechnol Bioeng 43:622–634CrossRefGoogle Scholar
  28. 28.
    Levin SA, Grenfell B, Hastings A, Perelson AS (1997) Mathematical and computational challenges in population biology and ecosystems science. Science 275:334–343CrossRefzbMATHGoogle Scholar
  29. 29.
    Levine JA, Paulsen RR, Zhang Y (2012) Mesh processing in medical-image analysis-A tutorial. IEEE Comput Graph Appl 32(5):22–28CrossRefGoogle Scholar
  30. 30.
    Levoy M (1990) Efficient ray tracing of volume data. ACM T Graphic 9:245–261CrossRefzbMATHGoogle Scholar
  31. 31.
    Linsen L, Pascucci V, Duchaineau MA, Hamann B, Joy KI, Coquillart S, Shum H-Y, Hu S-M (2002) Hierarchical representation of time-varying volume data with 4th-root-of-2 subdivision and quadrilinear B-spline wavelets. In Proceedings of the Tenth Pacific Conference on Computer Graphics and Applications – Pacific Graphics, 346Google Scholar
  32. 32.
    Lorensen WE, Cline HE (1987) Marching cubes: A high resolution 3-D surface construction algorithm. In Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’87), 163–169Google Scholar
  33. 33.
    Lum E, Ma K-L, Clyne J (2001) Texture hardware assisted rendering of time-varying volume data. In Proceedings of IEEE Conference on Visualization, 263–270Google Scholar
  34. 34.
    Lysaght MJ, Hazlehurst AL (2004) Tissue engineering: the end of the beginning. Tissue Eng 10:309–320CrossRefGoogle Scholar
  35. 35.
    Ma K-L (2003) Visualizing time-varying volume data. Comput Sci Eng 5:34–42CrossRefGoogle Scholar
  36. 36.
    Ma K-L (2009) In situ visualization at extreme scale: challenges and opportunities. IEEE Comput Graph Appl 29(6):14–19CrossRefGoogle Scholar
  37. 37.
    Ma K-L, Lum EB (2005) Techniques for visualizing time-varying volume data. In: Hansen CD, Johnson CR (eds) The visualization handbook. Elsevier, Boston, pp 511–531CrossRefGoogle Scholar
  38. 38.
    Ma K-L, Wang C, Yu H, Tikhonova A (2007) In-situ processing and visualization for ultrascale simulations. J Phys: Conf Ser 78(012043):1–11CrossRefGoogle Scholar
  39. 39.
    Majno G, Joris I (2004) Cells, tissues and disease: Principles of general pathology. Oxford University PressGoogle Scholar
  40. 40.
    Marée AF, Hogeweg P (2001) How amoeboids self-organize into a fruiting body: multicellular coordination in Dictyostelium Discoideum. Proc Natl Acad Sci U S A 98:3879–3883CrossRefGoogle Scholar
  41. 41.
    Martin P (1997) Wound healing – aiming for perfect skin regeneration. Science 276:75–81CrossRefGoogle Scholar
  42. 42.
    Měch R, Prusinkiewicz P (1996) Visual models of plants interacting with their environment. In Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’96), 397–410Google Scholar
  43. 43.
    Mooney DJ, Mikos AG (1999) Growing new organs. Sci Am 280:60–65CrossRefGoogle Scholar
  44. 44.
    Morris D, Sewell C, Barbagli F, Blevins N, Girod S, Salisbury K (2006) Visuohaptic simulation of bone surgery for training and evaluation. IEEE Comput Graph Appl 26(6):48–57CrossRefGoogle Scholar
  45. 45.
    National Institute of Standards and Technology. Visualization of tissue engineering. Accessed 10 June 2012
  46. 46.
    Palsson BO, Bhatia SN (2004) Tissue engineering. Pearson Prentice Hall, Upper Saddle RiverGoogle Scholar
  47. 47.
    Pieper SD, Halle M, Kikinis R (2004) 3D Slicer. In Proceedings of the IEEE International Symposium on Biomedical Imaging: Nano to Macro, Vol. 1, 632–635Google Scholar
  48. 48.
    Post FH, Vrolijk B, Hauser H, Laramee RS, Doleisch H (2003) The state of the art in flow visualization: feature extraction and tracking. Comput Graphics Forum 22:775–792CrossRefGoogle Scholar
  49. 49.
    Prusinkiewicz P, Hammel MS, Mjolsness E (1993) Animation of plant development. In Proceedings of the 20th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’93), 351–360Google Scholar
  50. 50.
    Rosenblum L, Earnshaw RA, Encarnacao J, Hagen H, Kaufman A, Klimenko SV, Nielson G, Post F, Thalmann D (1994) Scientific visualization: Advances and challenges. Academic PressGoogle Scholar
  51. 51.
    Schroeder S, Regli WC, Shokoufandeh A, Sun W (2003) Representation of porous artifacts for bio-medical applications. In Proceedings of the Eighth ACM Symposium on Solid Modeling and Applications, 254–257Google Scholar
  52. 52.
    Sewell C, Morris D, Blevins NH, Dutta S, Agarwal S, Barbagli F, Salisbury K (2008) Providing metrics and performance feedback in a surgical simulator. Comput Aided Surg 13(2):63–81CrossRefGoogle Scholar
  53. 53.
    Shen H-W, Chiang L-J, Ma K-L (1999) A fast volume rendering algorithm for time-varying fields using a time-space partitioning (TSP) tree. In Proceedings of IEEE Conference on Visualization, 371–378Google Scholar
  54. 54.
    Silver D, Wang X (1997) Tracking and visualizing turbulent 3-D features. IEEE T Vis Comput Gr 3:129–141CrossRefGoogle Scholar
  55. 55.
    Soll D, Wessels D (1998) Motion analysis of living cells: Techniques in modern biomedical microscopy. Wiley-Liss, New YorkGoogle Scholar
  56. 56.
    Squillacote AH (2008) The ParaView guide: A parallel visualization application. Kitware, IncGoogle Scholar
  57. 57.
    Sun W, Lal P (2002) Recent development on computer aided tissue engineering – a review. Comput Meth Prog Bio 67(2):85–103CrossRefGoogle Scholar
  58. 58.
    Sutton P, Hansen CD (1999) Isosurface extraction in time-varying fields using a temporal branch-on-need tree (T-BON). In Proceedings of the IEEE Conference on Visualization, 147–153Google Scholar
  59. 59.
    Tchuente M (1987) Computation on automata networks. In: Fogelman-Soulie F, Robert Y, Tchuente M (eds) Automata networks in computer science: Theory and applications. Princeton University PressGoogle Scholar
  60. 60.
    Telea AC (2008) Data visualization: Principles and practice. AK Peters Ltd., WellesleyGoogle Scholar
  61. 61.
    Terrill J, George WL, Griffin TJ, Hagedorn J, Kelso JT, Olano M, Peskin A, Satterfield S, Sims JS, Bullard JW, Dunkers J, Martys NS, O’Gallagher A, Haemer G (2009) Extending measurement science to interactive visualization environments. In: Zudilova-Seinstra E, Adriaansen T, Van Liere R (eds) Trends in interactive visualization: A state-of-the-art survey. Springer, pp 287–302Google Scholar
  62. 62.
    Totsuka T, Levoy M (1993) Frequency domain volume rendering. In Proceedings of the 20th annual conference on computer graphics and interactive techniques (SIGGRAPH’93), 271–278Google Scholar
  63. 63.
    Troy M, Röber N, Möller T, Celler A, Stella Atkins M (2001) 4D space-time techniques: A medical imaging case study. In Proceedings of the IEEE Conference on Visualization, 473–476Google Scholar
  64. 64.
    Tzeng F-Y, Ma K-L (2005) Intelligent feature extraction and tracking for visualizing large-scale 4D flow simulations. In Proceedings of the 2005 ACM/IEEE supercomputing conference, 6Google Scholar
  65. 65.
    Vacanti JP, Vacanti CA (1997) The challenge of tissue engineering. In: Lanza RP, Langer RL, Chick WL (eds) Principles of tissue engineering, Academic PressGoogle Scholar
  66. 66.
    Wang X, Devarajan V (2004) A honeycomb model for soft tissue deformation. In Proceedings of the 2004 ACM SIGGRAPH International Conference on Virtual Reality Continuum and its Applications in Industry (VRCAI’04), 257–260Google Scholar
  67. 67.
    Westover L (1990) Footprint evaluation for volume rendering. In Proceedings of the 17th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’90), 367–376Google Scholar
  68. 68.
    Wolfram S (1994) Cellular automata and complexity: Collected papers. Addison-WesleyGoogle Scholar
  69. 69.
    Woodring J, Wang C, Shen H-W (2003) High-dimensional direct rendering of time-varying volumes. In Proceedings of IEEE Conference on Visualization, 417–424Google Scholar
  70. 70.
    Wright H, Crompton RH, Kharche S, Wenisch P (2010) Steering and visualization: enabling technologies for computational science. Future Gener Comput Syst 26:506–513CrossRefGoogle Scholar
  71. 71.
    Younesy H, Möller T, Carr H (2005) Visualization of time-varying volumetric data using differential time-histogram table. In Proceedings of the fourth international workshop on volume graphics, 21–29Google Scholar
  72. 72.
    Zhang K, Damevski K, Venkatachalapathy V, Parker, S (2004) SCIRun2: a CCA framework for high performance computing. In Proceedings of the Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments, 72–79Google Scholar
  73. 73.
    Zhang L, Tang C, Song Y, Zhang A, Ramanathan M (2003) Vizcluster and its application on classifying gene expression data. Distrib Parallel Databases 13:73–97CrossRefzbMATHGoogle Scholar
  74. 74.
    Zygourakis K, Bizios R, Markenscoff P (1991) Proliferation of anchorage-dependent contact-inhibited cells: I. Development of theoretical models based on cellular automata. Biotechnol Bioeng 38:459–470CrossRefGoogle Scholar
  75. 75.
    Whitlock B, Favre JM, Meredith JS (2011) Parallel in situ coupling of simulation with a fully featured visualization system. In Proceedings of the Eurographics Symposium on Parallel Graphics and Visualization (EGPGV 2011), Llandudno, Wales, UK, 101–109Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.College of Computer & Information SciencesKing Saud UniversityRiyadhSaudi Arabia

Personalised recommendations