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

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.

[1]  C. Lohrisch,et al.  Relationship between tumor location and relapse in 6,781 women with early invasive breast cancer. , 2000, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[2]  M. Chaplain,et al.  Mathematical modelling of radiotherapy strategies for early breast cancer. , 2006, Journal of theoretical biology.

[3]  A. Anderson,et al.  A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion , 2005 .

[4]  W. Stetler-Stevenson,et al.  Proteases in invasion: matrix metalloproteinases. , 2001, Seminars in cancer biology.

[5]  Adam Finkelstein,et al.  Improving progressive view-dependent isosurface propagation , 2002, Comput. Graph..

[6]  Han-Wei Shen,et al.  A Near Optimal Isosurface Extraction Algorithm Using the Span Space , 1996, IEEE Trans. Vis. Comput. Graph..

[7]  Valerio Pascucci,et al.  Fast isocontouring for improved interactivity , 1996, VVS '96.

[8]  M. Chaplain,et al.  Mathematical modelling of tumour invasion and metastasis , 2000 .

[9]  William E. Lorensen,et al.  Marching cubes: a high resolution 3D surface construction algorithm , 1996 .

[10]  R. A. ANDERSONa,et al.  Mathematical Modelling of Tumour Invasion and Metastasis , 2022 .

[11]  Jayaram K. Udupa,et al.  Surface Shading in the Cuberille Environment , 1985, IEEE Computer Graphics and Applications.

[12]  Paolo Cignoni,et al.  Speeding Up Isosurface Extraction Using Interval Trees , 1997, IEEE Trans. Vis. Comput. Graph..

[13]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.