{"title":"Identifying a response parameter in a model of brain tumor evolution under therapy","authors":"","doi":"10.1093/imamat/hxad013","DOIUrl":null,"url":null,"abstract":"\n A nonlinear conjugate gradient method is derived for the inverse problem of identifying a treatment parameter in a nonlinear model of reaction-diffusion type corresponding to the evolution of brain tumors under therapy. The treatment parameter is reconstructed from additional information about the tumour taken at a fixed instance of time. Well-posedness of the direct problems used in the iterative method is outlined as well as uniqueness of a solution to the inverse problem. Moreover, the parameter identification is recast as the minimization of a Tikhonov type functional and the existence of a minimizer to this functional is shown. Finite difference discretization of the space and time derivatives are employed for the numerical implementation. Numerical simulations on full 3-dimensional brain data is included showing that information about a spacewise dependent treatment parameter can be recovered in a stable way.","PeriodicalId":56297,"journal":{"name":"IMA Journal of Applied Mathematics","volume":"1 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IMA Journal of Applied Mathematics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/imamat/hxad013","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 1
Abstract
A nonlinear conjugate gradient method is derived for the inverse problem of identifying a treatment parameter in a nonlinear model of reaction-diffusion type corresponding to the evolution of brain tumors under therapy. The treatment parameter is reconstructed from additional information about the tumour taken at a fixed instance of time. Well-posedness of the direct problems used in the iterative method is outlined as well as uniqueness of a solution to the inverse problem. Moreover, the parameter identification is recast as the minimization of a Tikhonov type functional and the existence of a minimizer to this functional is shown. Finite difference discretization of the space and time derivatives are employed for the numerical implementation. Numerical simulations on full 3-dimensional brain data is included showing that information about a spacewise dependent treatment parameter can be recovered in a stable way.
期刊介绍:
The IMA Journal of Applied Mathematics is a direct successor of the Journal of the Institute of Mathematics and its Applications which was started in 1965. It is an interdisciplinary journal that publishes research on mathematics arising in the physical sciences and engineering as well as suitable articles in the life sciences, social sciences, and finance. Submissions should address interesting and challenging mathematical problems arising in applications. A good balance between the development of the application(s) and the analysis is expected. Papers that either use established methods to address solved problems or that present analysis in the absence of applications will not be considered.
The journal welcomes submissions in many research areas. Examples are: continuum mechanics materials science and elasticity, including boundary layer theory, combustion, complex flows and soft matter, electrohydrodynamics and magnetohydrodynamics, geophysical flows, granular flows, interfacial and free surface flows, vortex dynamics; elasticity theory; linear and nonlinear wave propagation, nonlinear optics and photonics; inverse problems; applied dynamical systems and nonlinear systems; mathematical physics; stochastic differential equations and stochastic dynamics; network science; industrial applications.