Image-Driven Biophysical Tumor Growth Model Calibration

DOI10.1137/19M1275280zbMath1453.35114arXiv1907.07774OpenAlexW3104726708WikidataQ100725840 ScholiaQ100725840MaRDI QIDQ5112560

Miriam Mehl, Klaudius Scheufele, George Biros, Andreas Mang, Shashank Subramanian

Publication date: 29 May 2020

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.07774

zbMATH Keywords

Picard iterationimage registrationPDE-constrained optimizationbiophysical model calibrationtumor progression inversion

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Nonlinear parabolic equations (35K55) Spectral, collocation and related methods for boundary value problems involving PDEs (65N35) Medical applications (general) (92C50) Parallel numerical computation (65Y05) Numerical methods of relaxation type (49M20) Initial-boundary value problems for second-order parabolic systems (35K51)

Related Items

An operator-splitting approach for variational optimal control formulations for diffeomorphic shape matching ⋮ Image-Driven Biophysical Tumor Growth Model Calibration ⋮ Deep learning characterization of brain tumours with diffusion weighted imaging

Uses Software

• PETSc
• TAO
• AccFFT
• CLAIRE
• FAIR.m

Cites Work

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