Keynotes
| V01: Image Registration for a Dynamic Breathing Model Pia Schulz et al. University of Lübeck |
| V02: Abstract: ConvexAdam, a Self-Configuring Framework for Dual-Optimisation-Based 3D Multitask Medical Image Registration Christoph Großbröhmer et al. University of Lübeck |
| ★ V03: Surrogate-based Respiratory Motion Estimation Using Physics-Enhanced Implicit Neural Representations Jan Boysen et al. German Research Center for Artificial Intelligence |
Session 2: Video Analysis
| V04: Comparison of framewise video-classification approaches in laryngoscopies Ole Felber et al. University Medical Center Hamburg-Eppendorf |
| V05: Realtime Fiberscopic Image Improvement for Automated Lesion Detection in the Urinary Bladder Thomas Eixelberger et al. Frauenhofer IIS & FAU Erlangen |
| V06: A Universal and Flexible Framework for Unsupervised Statistical Shape Model Learning Nafie El Amrani et al. University of Bonn |
| V07: Robust Statistical Shape Modelling with Implicit Neural Representations Christoph Großbröhmer et al. University of Lübeck |
| ★ V08: iRBSM: A Deep Implicit 3D Breast Shape Model Maximilian Weiherer et al. FAU Erlangen-Nürnberg & OTH Regensburg |
Session 4: Generative Models
| V09: Diffusion Models for Conditional Brain Tumor MRI Generation with Tumor-induced Deformations Mona Irsfeld et al. German Research Center for Artificial Intelligence |
| ★ V10: LLM-Driven Baselines for Medical Image Segmentation Jasmin Arjomandi et al. FAU Erlangen-Nürnberg |
| V11: Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models Zeineb Haouari et al. Technical University of Munich |
Session 5: Improving Reliability
| V12: Is Self-Supervision Enough? Benchmarking Foundation Models Against End-to-End Training for Mitotic Figure Classification Jonathan Ganz et al. Technische Hochschule Ingolstadt |
| V13: Look - No Convs! Mattias Heinrich University of Lübeck |
| V14: Abstract: Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model Luisa Gallée et al. Ulm University Medical Center |
| V15: Evaluating the Fidelity of Explanations for Convolutional Neural Networks in Alzheimer’s Disease Detection Bjarne Hiller et al. German Center for Neurodegenerative Diseases (DZNE) |
| V16: Metrics Reloaded: Recommendations and Online Toolkit for Image Analysis Validation Emre Kavur et al. German Cancer Research Center (DKFZ) |
| I01: Are LLMs Killing the Knowledge Graph? Clinical NLP Between Distributional and Symbolic Representation Sven Büchel, Drazenko Djordjevic ID GmbH |
| V17: Real-Time Landmark Guidance for Radial Head Localization in Ultrasound Imaging Lennart Meyling et al. University of Lübeck |
| V18: Ultrasound-based 3D Reconstruction of Residual Limbs using Electromagnetic Tracking Pauline Heine et al. Ulm University of Applied |
| ★ V19: Autocalibration for 3D Ultrasound Reconstruction in Infant Hip Dysplasia Screening Wiebke Heyer et al. University of Lübeck |
| V20: Weakly Supervised Segmentation of HRF in OCT with Compact Convolutional Transformers and SAM 2 Olivier Morelle et al. University of Bonn |
| ★ V21: Bridging Gaps in Retinal Imaging Timo Kepp et al. German Research Center for Artificial Intelligence |
| ★ V22: AMI-Br: A Dataset of Typical and Atypical Mitotic Figures on Human Breast Cancer Christof Bertram et al. University of Veterinary Medicine Vienna |
| ★ V24: Automation Bias in AI-Assisted Medical Decision-Making under Time Pressure in Computational Pathology Emely Rosbach et al. Technische Hochschule Ingolstadt |
| V25: Re-identification from histopathology Images Jonathan Ganz et al. Technische Hochschule Ingolstadt |
| V26: AnatoMix: Anatomy-aware Data Augmentation for Multi-organ Segmentation in CT Chang Liu et al. FAU Erlangen-Nürnberg |
| V27: Segmentation of Spinal Necrosis Zones in MRI Janine Hürtgen et al. Otto von Guericke University Magdeburg |
| V28: Investigating Augmented Reality Prompts for Foundation Model based Semantic Segmentation Michael Schwimmbeck et al. University of Applied Sciences Landshut |
| V29: nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation Fabian Isensee et al. German Cancer Research Center (DKFZ) |
★: Im Begutachtungsprozess unter den sieben besten Beiträgen