Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration

Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration

We discuss solution algorithms for calibrating a tumor growth model using imaging data posed as a deterministic inverse problem. The forward model consists of a nonlinear and time-dependent reaction-diffusion partial differential equation (PDE) with unknown parameters (diffusivity and proliferation...

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Hauptverfasser: Liang, Baoshan, Lozenski, Luke, Villa, Umberto, Faghihi, Danial
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Mathematics - Optimization and Control
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Lozenski, Luke
Villa, Umberto
Faghihi, Danial
description We discuss solution algorithms for calibrating a tumor growth model using imaging data posed as a deterministic inverse problem. The forward model consists of a nonlinear and time-dependent reaction-diffusion partial differential equation (PDE) with unknown parameters (diffusivity and proliferation rate) being spatial fields. We use a dimension-independent globalized, inexact Newton Conjugate Gradient algorithm to solve the PDE-constrained optimization. The required gradient and Hessian actions are also presented using the adjoint method and Lagrangian formalism.
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title Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration
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