6 papers
Multimodal classification of Radiation-Induced Contrast Enhancements and tumor recurrence using deep learning
Robin Peretzke, Marlin Hanstein, Maximilian Fischer +15
The differentiation between tumor recurrence and radiation-induced contrast enhancements in post-treatment glioblastoma patients remains a major clinical challenge. Existing approa…
CRONOS: Continuous Time Reconstruction for 4D Medical Longitudinal Series
Nico Albert Disch, Saikat Roy, Constantin Ulrich +5
Forecasting how 3D medical scans evolve over time is important for disease progression, treatment planning, and developmental assessment. Yet existing models either rely on a singl…
Temporal Flow Matching for Learning Spatio-Temporal Trajectories in 4D Longitudinal Medical Imaging
Nico Albert Disch, Yannick Kirchhoff, Robin Peretzke +5
Understanding temporal dynamics in medical imaging is crucial for applications such as disease progression modeling, treatment planning and anatomical development tracking. However…
Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes
Maximilian Fischer, Florian M. Hauptmann, Robin Peretzke +4
Although advances in brain surgery techniques have led to fewer postoperative complications requiring Intensive Care Unit (ICU) monitoring, the routine transfer of patients to the…
Unlocking the Potential of Digital Pathology: Novel Baselines for Compression
Maximilian Fischer, Peter Neher, Peter Schüffler +13
Digital pathology offers a groundbreaking opportunity to transform clinical practice in histopathological image analysis, yet faces a significant hurdle: the substantial file sizes…
An OpenMind for 3D medical vision self-supervised learning
Tassilo Wald, Constantin Ulrich, Jonathan Suprijadi +5
The field of self-supervised learning (SSL) for 3D medical images lacks consistency and standardization. While many methods have been developed, it is impossible to identify the cu…