Visualisation of the numerical solution of partial differential equation systems in three space dimensions and its importance for mathematical models in biology

  • Received: 01 November 2005 Accepted: 29 June 2018 Published: 01 August 2006
  • MSC : 76M27,92B05,92C15,92C50.

  • Numerical analysis and computational simulation of partial differential equation models in mathematical biology are now an integral part of the research in this field. Increasingly we are seeing the development of partial differential equation models in more than one space dimension, and it is therefore necessary to generate a clear and effective visualisation platform between the mathematicians and biologists to communicate the results. The mathematical extension of models to three spatial dimensions from one or two is often a trivial task, whereas the visualisation of the results is more complicated. The scope of this paper is to apply the established marching cubes volume rendering technique to the study of solid tumour growth and invasion, and present an adaptation of the algorithm to speed up the surface rendering from numerical simulation data. As a specific example, in this paper we examine the computational solutions arising from numerical simulation results of a mathematical model of malignant solid tumour growth and invasion in an irregular heterogeneous three-dimensional domain, i.e., the female breast. Due to the different variables that interact with each other, more than one data set may have to be displayed simultaneously, which can be realized through transparency blending. The usefulness of the proposed method for visualisation in a more general context will also be discussed.

    Citation: Heiko Enderling, Alexander R.A. Anderson, Mark A.J. Chaplain, Glenn W.A. Rowe. Visualisation of the numerical solution of partial differential equation systems in three space dimensions and its importance for mathematical models in biology[J]. Mathematical Biosciences and Engineering, 2006, 3(4): 571-582. doi: 10.3934/mbe.2006.3.571

    Related Papers:

    [1] Maria Vittoria Barbarossa, Christina Kuttler, Jonathan Zinsl . Delay equations modeling the effects of phase-specific drugs and immunotherapy on proliferating tumor cells. Mathematical Biosciences and Engineering, 2012, 9(2): 241-257. doi: 10.3934/mbe.2012.9.241
    [2] Salvador Chulián, Álvaro Martinez-Rubio, María Luz Gandarias, María Rosa . Lie point symmetries for generalised Fisher's equations describing tumour dynamics. Mathematical Biosciences and Engineering, 2021, 18(4): 3291-3312. doi: 10.3934/mbe.2021164
    [3] Azmy S. Ackleh, Mark L. Delcambre, Karyn L. Sutton, Don G. Ennis . A structured model for the spread of Mycobacterium marinum: Foundations for a numerical approximation scheme. Mathematical Biosciences and Engineering, 2014, 11(4): 679-721. doi: 10.3934/mbe.2014.11.679
    [4] H. Thomas Banks, W. Clayton Thompson, Cristina Peligero, Sandra Giest, Jordi Argilaguet, Andreas Meyerhans . A division-dependent compartmental model for computing cell numbers in CFSE-based lymphocyte proliferation assays. Mathematical Biosciences and Engineering, 2012, 9(4): 699-736. doi: 10.3934/mbe.2012.9.699
    [5] Weidong Zhao, Mobeen Munir, Ghulam Murtaza, Muhammad Athar . Lie symmetries of Benjamin-Ono equation. Mathematical Biosciences and Engineering, 2021, 18(6): 9496-9510. doi: 10.3934/mbe.2021466
    [6] Krzysztof Fujarewicz, Krzysztof Łakomiec . Adjoint sensitivity analysis of a tumor growth model and its application to spatiotemporal radiotherapy optimization. Mathematical Biosciences and Engineering, 2016, 13(6): 1131-1142. doi: 10.3934/mbe.2016034
    [7] Azmy S. Ackleh, Linda J. S. Allen, Graciela Canziani, Shandelle M. Henson, Jia Li, Zhien Ma . Preface. Mathematical Biosciences and Engineering, 2008, 5(4): i-iii. doi: 10.3934/mbe.2008.5.4i
    [8] Avner Friedman, Wenrui Hao . Mathematical modeling of liver fibrosis. Mathematical Biosciences and Engineering, 2017, 14(1): 143-164. doi: 10.3934/mbe.2017010
    [9] Jimin Yu, Jiajun Yin, Shangbo Zhou, Saiao Huang, Xianzhong Xie . An image super-resolution reconstruction model based on fractional-order anisotropic diffusion equation. Mathematical Biosciences and Engineering, 2021, 18(5): 6581-6607. doi: 10.3934/mbe.2021326
    [10] M. B. A. Mansour . Computation of traveling wave fronts for a nonlinear diffusion-advection model. Mathematical Biosciences and Engineering, 2009, 6(1): 83-91. doi: 10.3934/mbe.2009.6.83
  • Numerical analysis and computational simulation of partial differential equation models in mathematical biology are now an integral part of the research in this field. Increasingly we are seeing the development of partial differential equation models in more than one space dimension, and it is therefore necessary to generate a clear and effective visualisation platform between the mathematicians and biologists to communicate the results. The mathematical extension of models to three spatial dimensions from one or two is often a trivial task, whereas the visualisation of the results is more complicated. The scope of this paper is to apply the established marching cubes volume rendering technique to the study of solid tumour growth and invasion, and present an adaptation of the algorithm to speed up the surface rendering from numerical simulation data. As a specific example, in this paper we examine the computational solutions arising from numerical simulation results of a mathematical model of malignant solid tumour growth and invasion in an irregular heterogeneous three-dimensional domain, i.e., the female breast. Due to the different variables that interact with each other, more than one data set may have to be displayed simultaneously, which can be realized through transparency blending. The usefulness of the proposed method for visualisation in a more general context will also be discussed.


  • This article has been cited by:

    1. Natalia L. Komarova, Dominik Wodarz, 2014, Chapter 1, 978-1-4614-8300-7, 1, 10.1007/978-1-4614-8301-4_1
    2. Heiko Enderling, Jayant S. Vaidya, 2008, Chapter 13, 978-0-8176-4712-4, 1, 10.1007/978-0-8176-4713-1_13
    3. Rui Li, Bei Hu, A parabolic–hyperbolic system modeling the growth of a tumor, 2019, 267, 00220396, 693, 10.1016/j.jde.2019.01.020
    4. Jiayue Zheng, Ruixiang Xing, Bifurcation for a free-boundary tumor model with extracellular matrix and matrix degrading enzymes, 2020, 268, 00220396, 3152, 10.1016/j.jde.2019.09.055
    5. Mikhail K. Kolev, Miglena N. Koleva, Lubin G. Vulkov, Two positivity preserving flux limited, second-order numerical methods for a haptotaxis model, 2013, 29, 0749159X, 1121, 10.1002/num.21748
    6. Alexander R. A. Anderson, 2007, Chapter 1, 978-3-7643-8101-1, 3, 10.1007/978-3-7643-8123-3_1
    7. Heiko Enderling, Alexander R.A. Anderson, Mark A.J. Chaplain, A model of breast carcinogenesis and recurrence after radiotherapy, 2007, 7, 16177061, 1121701, 10.1002/pamm.200700362
    8. V.S.K. Manem, M. Kohandel, N.L. Komarova, S. Sivaloganathan, Spatial invasion dynamics on random and unstructured meshes: Implications for heterogeneous tumor populations, 2014, 349, 00225193, 66, 10.1016/j.jtbi.2014.01.009
    9. Markus Karlsson, David L.I. Janzén, Lucia Durrieu, Alejandro Colman-Lerner, Maria C. Kjellsson, Gunnar Cedersund, Nonlinear mixed-effects modelling for single cell estimation: when, why, and how to use it, 2015, 9, 1752-0509, 10.1186/s12918-015-0203-x
  • Reader Comments
  • © 2006 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3170) PDF downloads(551) Cited by(9)

Article outline

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog