Personalized Brain Tumor Modeling with Deep Neural Networks

Brain tumors are complex and heterogeneous, making accurate modeling and prediction of their growth challenging. In this paper, we study a deep learning approach so called physics-informed neural network (PINN) for personalized brain tumor modeling that incorporates both patient-specific data and the underlying physics of tumor growth. We demonstrate the effectiveness of our approach on a synthetic dataset of brain tumor in one-dimension.