Numerical Algorithm of Effective Cancer Treatment Based on the Fisher-Kolmogorov Equation

12 pages•Published: December 11, 2024

Andrey Kovtanyuk, Christina Kuttler and Alexander Chebotarev

Abstract

An inverse extremal problem for the Fisher-Kolmogorov model of tumor growth is studied. It is required to minimize the normalized density of tumor cells in a given subdomain, while the drug concentration in the tissue must be limited to specified values. The solvability of the inverse extremal problem is established. An algorithm to find its solution is constructed. The numerical experiments illustrate its efficiency.

Keyphrases: finite element modeling, fisher kolmogorov model of tumor growth, iterative algorithm, optimal control

In: Varvara L Turova, Andrey E Kovtanyuk and Johannes Zimmer (editors). Proceedings of 3rd International Workshop on Mathematical Modeling and Scientific Computing, vol 104, pages 163-174.

Links:	https://easychair.org/publications/paper/3dhj
	https://doi.org/10.29007/z3mk

BibTeX entry

@inproceedings{MMSC2024:Numerical_Algorithm_Effective_Cancer,
  author    = {Andrey Kovtanyuk and Christina Kuttler and Alexander Chebotarev},
  title     = {Numerical Algorithm of Effective Cancer Treatment Based on the Fisher-Kolmogorov Equation},
  booktitle = {Proceedings of  3rd International Workshop on Mathematical Modeling and Scientific Computing},
  editor    = {Varvara L Turova and Andrey E Kovtanyuk and Johannes Zimmer},
  series    = {EPiC Series in Computing},
  volume    = {104},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/3dhj},
  doi       = {10.29007/z3mk},
  pages     = {163-174},
  year      = {2024}}

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