Abstract
The paper focuses on a numerical method for detecting, visualizing and monitoring abnormal cell growth using large-scale mathematical simulations. The discretization of multi-dimensional partial differential equation (PDE) is based on finite difference method. The predictor system depending on users input data via a user interface, generating the initial and boundary condition generated from parabolic or elliptic type of PDE. The processing large sparse matrixes are based on multiprocessor computer systems for abnormal growth visualization. The multi-dimensional abnormal cell has produced the numerical analysis and understanding results at the target area for the potential improvement of detection and monitoring the growth. The development of the prediction system is the combinations of the parallel algorithms, open source software on Linux environment and distributed multiprocessor system. The paper ends with a concluding remark on the parallel performance evaluations and numerical analysis in reducing the execution time, communication cost and computational complexity.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Andrew, M.S., Demuth, T., Mobley, D., Berens, M., Leonard, M.S.: A Mathematical Model of Glioblastoma Tumor Spheroid Invasion in a Three-Dimensional In Vitro Experiment. Biophysical Journal 92, 356–365 (2007)
Angelis, E.D., Preziosi, L.: Advection-Diffusion Models for Solid Tumour Evolution in Vivo and Related Free Boundary Problem. Mathematical Models and Methods in Applied Sciences 10(3), 379–407 (2000)
Chato, J.C.: Fundamentals of bioheat transfer. In: Gautherie, M. (ed.) Thermal dosimetry and treatment planning, pp. 1–56. Springer, Berlin (1990)
Norma, A., bin Masseri, M.I.S., Rajibul Islam, M., Khalid, S.N.: The Visualization of Three Dimensional Brain Tumors’ Growth on Distributed Parallel Computer Systems. Journal of Applied Sciences. Asian Network for Scientific Information (ANSINET) 9(3), 505–512 (2009)
Norma, A., Norfarizan, M.S., Pheng, H.S.: High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems. Journal of Information Technology and Multimedia 4, 39–52 (2007)
Sahimi, M.S., Mansor, N.A., Nor, N.M., Nusi, N.M., Norma, A.: A High accuracy variant of the Iterative Alternating Decomposition Explicit Method for Solving the Heat Equation. International Journal of Simulation and processing Modelling 2(½), 45–49 (2006)
Norma, A., Norfarizan, Hidayah, S.N.K., Dolly, S., Phang, T.I.: The parallelism algorithm of human tumor growth using high performance computing. In: The 2nd International Conference on Pervasive Computing Technologies for Healthcare, Tampere, Finland (2008)
Norma, A., Norfarizan, M.S., Hidayah, S.N.K.: High Performance Visualization of Human Tumor Growth Software. In: Palma, J.M.L.M., Amestoy, P.R., Daydé, M., Mattoso, M., Lopes, J.C. (eds.) VECPAR 2008. LNCS, vol. 5336, pp. 591–599. Springer, Heidelberg (2008)
Evans, D.J., Sahimi, M.S.: The Alternating Group Explicit Iterative method for Solving Parabolic Equations. Intern. J. Computer math. 24, 127–145 (1988)
Swanson, K., Alvord, E., Murray, J.D.: A Quantitative Model for Differential Motility of Gliomas in Grey and White Matter. Cell Prolif. 33, 317–329 (2000)
Bellomo, N., Preziosi, L.: Modeling and mathematical problems related to tumor evolution and its interaction with the immune system. Math. Comput. Modelling 32, 413–452 (2000)
Murray, J.D.: Mathematical Biology, 2nd edn. Biomathematics, vol. 19. Springer, Berlin (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alias, N. et al. (2010). Parallel System for Abnormal Cell Growth Prediction Based on Fast Numerical Simulation. In: Hsu, CH., Malyshkin, V. (eds) Methods and Tools of Parallel Programming Multicomputers. MTPP 2010. Lecture Notes in Computer Science, vol 6083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14822-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-642-14822-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14821-7
Online ISBN: 978-3-642-14822-4
eBook Packages: Computer ScienceComputer Science (R0)