Programme 

Oral Session 1 — 10 min Pre & 2 min QA

1. Thomas Boucher: From O(n²) to O(n) Parameters: Quantum Self-Attention in Vision Transformers for Biomedical Image Classification

2. Zhe Min: DetSAM: A Joint Detection-and-Segmentation Learning Framework for Multi-Class Surgical Instrument Segmentation

3. Tom Vercauteren: Beyond One-hot Encoding? Journey into Compact Encoding for Large Multi-class Segmentation

4. Boxuan Li: Efficient Foundation Model Pre-training on Mixed Retina Images from Similar Modalities

5. Hongqiu Wang: Towards Efficient and Privacy-Preserving Medical Image Segmentation: A Point-Driven Source-Free Active Adaptation Framework

Oral Session 2 — 10 min Pre & 2 min QA

1. Michael Deutges: Neural Cellular Automata for Weakly Supervised Segmentation of White Blood Cells

2. Mostafa Mehdipour Ghazi: RARE-UNet: Resolution-Aligned Routing Entry for Adaptive Medical Image Segmentation

3. Yucheng Tang: Impact of Clinical Image Quality on Efficient Foundation Model Finetuning

4. Jiacheng Hou: BrainNetMLP: An Efficient and Effective Baseline for Functional Brain Network Classification

5. Yang Yang: Triple Expert Adaptation Networks with Adaptive Prompt Selection for Multi-Modal Medical Image Fusion

Closing Remarks & Award Session