Supervised Contrastive Learning for Image-to-Graph Transformers. - Anna Banaszak; Alexander H. Berger; Laurin Lux; Suprosanna Shit; Daniel Rueckert; Johannes C. Paetzold (GRAIL@MICCAI, 2024)

Topologically Faithful Multi-class Segmentation in Medical Images. - Alexander H. Berger; Laurin Lux; Nico Stucki; Vincent Bürgin; Suprosanna Shit; Anna Banaszak; Daniel Rueckert; Ulrich Bauer; Johannes C. Paetzold (MICCAI (8), 2024)

Exploring Graphs as Data Representation for Disease Classification in Ophthalmology. - Laurin Lux; Alexander H. Berger; Maria Romeo Tricas; Martin J. Menten; Daniel Rueckert; Johannes C. Paetzold (GRAIL@MICCAI, 2024)

Spatial Brain Tumor Concentration Estimation for Individualized Radiotherapy Planning. - Jonas Weidner; Michal Balcerak; Ivan Ezhov; André Datchev; Laurin Lux; Lucas Zimmer; Daniel Rückert; Bjoern H. Menze; Benedikt Wiestler (CoRR, 2024)

Topograph: An Efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation. - Laurin Lux; Alexander H. Berger; Alexander Weers; Nico Stucki; Daniel Rueckert; Ulrich Bauer; Johannes C. Paetzold (ICLR, 2025)

Pitfalls of Topology-Aware Image Segmentation. - Alexander H. Berger; Laurin Lux; Alexander Weers; Martin J. Menten; Daniel Rueckert; Johannes C. Paetzold (IPMI (1), 2025)

Cross-Domain and Cross-Dimension Learning for Image-to-Graph Transformers. - Alexander H. Berger; Laurin Lux; Suprosanna Shit; Ivan Ezhov; Georgios Kaissis; Martin J. Menten; Daniel Rueckert; Johannes C. Paetzold (WACV, 2025)

Interpretable Retinal Disease Prediction Using Biology-Informed Heterogeneous Graph Representations. - Laurin Lux; Alexander H. Berger; Maria Romeo Tricas; Alaa E. Fayed; Sobha Sivaprasad; Linus Kreitner; Jonas Weidner; Martin J. Menten; Daniel Rueckert; Johannes C. Paetzold (CoRR, 2025)

Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis. - Chenjun Li; Laurin Lux; Alexander H. Berger; Martin J. Menten; Mert R. Sabuncu; Johannes C. Paetzold (CoRR, 2025)

From Pixels to Histopathology: A Graph-Based Framework for Interpretable Whole Slide Image Analysis. - Alexander Weers; Alexander H. Berger; Laurin Lux; Peter Schüffler; Daniel Rueckert; Johannes C. Paetzold (CoRR, 2025)

A Learnable Prior Improves Inverse Tumor Growth Modeling. - Jonas Weidner; Ivan Ezhov; Michal Balcerak; Marie-Christin Metz; Sergey Litvinov; Sebastian Kaltenbach; Leonhard F. Feiner; Laurin Lux; Florian Kofler; Jana Lipková; Jonas Latz; Daniel Rueckert; et al. (IEEE Trans. Medical Imaging, 2025)