MEDICAL IMAGING MEETS EURIPS
An official EurIPS Workshop - 07 December 2025
An official EurIPS Workshop - 07 December 2025
08:30 – 08:45 Opening Remarks - Nina Weng
08:45 – 09:30 Dr. Veronika Cheplygina
Title: Curious Findings About Medical Image Datasets
09:30 – 10:00 Poster Pitch Session (18 papers - 1.5 mins each)
10:00 – 11:00 Poster Session 1
11:00 – 11:45 Dr. Daniel Coelho de Castro - Session Chair: Eitan Waks
Title: From Medical Image Interpretation to Scientific Discovery
11:45 – 12:30 Dr. Christian F. Baumgartner
Title: Making AI Make Sense: Concept-Based Pathology Diagnosis and Uncertainty-Aware MRI
12:30 – 13:30 Lunch/break
13:30 – 15:00 Long Oral Session (7 papers - 10 mins + 2 mins QA) - Session Chair: Nina Weng
15:00 – 16:00 Poster Session 2
16:00 – 16:50 Panel Discussion
16:55 – 17:00 Closing Remark
Long Orals:
1. “When are radiology reports useful for training medical image classifiers?”, Herman Bergström, Zhongqi Yue, Fredrik D. Johansson.
2. “TGV: Tabular Data-Guided Learning of Visual Cardiac Representations”, Marta Hasny, Maxime Di Folco, Keno Bressem, Julia Schnabel.
3. “Visual Semantics Meets Medical Diagnosis: Cross-Scale Embedding Alignment for Clinically Explainable Medical Image Segmentation”, Thuraya Alzubaidi, Muzammil Behzad.
4. “We Need to Talk About Functional Brain Networks”, Gurur Gamgam.
5. “Who Does Your Algorithm Fail? Investigating Age and Ethnic Bias in the MAMA-MIA Dataset”, Aditya Parikh, Sneha Das, Aasa Feragen.
6. “CARE: Confidence-aware Ratio Estimation for Medical Biomarkers”, Jiameng Li, Teodora Popordanoska, Aleksei Tiulpin, Sebastian Gruber, Frederik Maes, Matthew B. Blaschko.
7. “Reliable Cell Trackers Say "I dunno!"”, Richard D. Paul, Johannes Seiffarth, David Rügamer, Hanno Scharr, Katharina Nöh.
Spotlight (Poster Pitch Session):
1. “Improving Polyp Classification in Colonoscopy using Self-Supervised Learning with Side Information”,
2. “Bayesian generative models can flag performance loss and bias”
3. “Evaluation of Time-of-Flight Camera Positioning for AI-based Patient Pose Assessment in Radiography”
4. “Clinically-Guided Counterfactuals (C³): Physics and Pathology-Aware Augmentation and Evaluation for Robust Medical Imaging Models”
5. “Mitigating Representation Bottlenecks in Multiple Instance Learning”
6. “Accounting for Underspecification in Statistical Claims of Model Superiority”
7. “Hyperbolic Representation Learning for Spatial Biology: Capturing Cell Type Hierarchies in Breast Cancer”
8. “LAND: Lung and Nodule Diffusion for 3D Chest CT Synthesis with Anatomical Guidance
Mitigating Representation Bottlenecks in Multiple Instance Learning”
9. “Metadata-Aligned 3D MRI Representations for Contrast and Sequence Understanding”
10. “An Efficient One-Shot Federated Medical Imaging via Variational Inference Parametric Feature Transfer”
11. “Conditioned Implicit Neural Representation for Regularized Deformable Image Registration”
12. “Causal Attribution of Model Performance Gaps in Medical Imaging Under Distribution Shifts”
13.” Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction”
14. “Looking Beyond Aggregation for Medical Federated Learning: From Analysis to Novel Architecture Design”
15. “How Reliable Are Networks? A Bayesian Modeling Approach”
16. “Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation”
17. “Polyp Segmentation Using Wavelet-Based Cross-Band Integration for Enhanced Boundary Representation”
18. “Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN”