Personalized Predictions of Glioblastoma Infiltration: Mathematical
Models, Physics-Informed Neural Networks and Multimodal Scans

Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans

28 November 2023

Ray Zirui Zhang

Michal Balcerak

Benedikt Wiestler

Bjoern H. Menze

John S. Lowengrub

Papers citing "Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans"

5 / 5 papers shown

Title
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization Michal Balcerak Tamaz Amiranashvili Andreas Wagner Jonas Weidner Petr Karnakov Johannes C. Paetzold Ivan Ezhov Petros Koumoutsakos Benedikt Wiestler Bjoern H. Menze AI4CE 22 2 0 30 Sep 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 68 1 0 27 Apr 2024
A Learnable Prior Improves Inverse Tumor Growth Modeling Jonas Weidner Ivan Ezhov Michal Balcerak M. Metz Sergey Litvinov ... Jana Lipkova Jonas Latz Daniel Rueckert Bjoern H. Menze Benedikt Wiestler MedIm AI4CE 21 5 0 07 Mar 2024
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 238 2,298 0 18 Oct 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 183 760 0 13 Mar 2020