4 papers
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…
A Biophysically-Conditioned Generative Framework for 3D Brain Tumor MRI Synthesis
Valentin Biller, Lucas Zimmer, Ayhan Can Erdur +4
Magnetic resonance imaging (MRI) inpainting supports numerous clinical and research applications. We introduce the first generative model that conditions on voxel-level, continuous…
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation
Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter +8
Neural implicit k-space representations have shown promising results for dynamic MRI at high temporal resolutions. Yet, their exclusive training in k-space limits the application o…
(Predictable) Performance Bias in Unsupervised Anomaly Detection
Felix Meissen, Svenja Breuer, Moritz Knolle +5
Background: With the ever-increasing amount of medical imaging data, the demand for algorithms to assist clinicians has amplified. Unsupervised anomaly detection (UAD) models promi…