7 citations · 18 across the 11 of their papers we have counts for
4 papers · 1 filter
TumorFlow: Physics-Guided Longitudinal MRI Synthesis of Glioblastoma Growth
Valentin Biller, Niklas Bubeck, Lucas Zimmer +6
Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only partially visible on routine MRI, making it difficult to reliably assess true tumor…
Interpretable Retinal Disease Prediction Using Biology-Informed Heterogeneous Graph Representations
Laurin Lux, Alexander H. Berger, Maria Romeo Tricas +8
Interpretability is crucial for utilizing machine learning models as clinical decision support tools for medical diagnostics. However, most state-of-the-art image classifiers based…
Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models
Zeineb Haouari, Jonas Weidner, Yeray Martin-Ruisanchez +5
Glioblastoma, a highly aggressive brain tumor, poses major challenges due to its poor prognosis and high morbidity rates. Partial differential equation-based models offer promising…
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner +7
Physical models in the form of partial differential equations serve as important priors for many under-constrained problems. One such application is tumor treatment planning, which…