Statistical Motion Mask and Sliding Registration. - Björn Eiben; Elena H. Tran; Martin J. Menten; Uwe Oelfke; David J. Hawkes; Jamie R. McClelland (WBIR, 2018)

Deep Learning Prediction Of Age And Sex From Optical Coherence Tomography. - Osama N. Hassan; Martin J. Menten; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Andrew J. Lotery; Daniel Rueckert (ISBI, 2021)

Automated Analysis of Diabetic Retinopathy Using Vessel Segmentation Maps as Inductive Bias. - Linus Kreitner; Ivan Ezhov; Daniel Rueckert; Johannes C. Paetzold; Martin J. Menten (MIDOG/DRAC@MICCAI, 2022)

Physiology-Based Simulation of the Retinal Vasculature Enables Annotation-Free Segmentation of OCT Angiographs. - Martin J. Menten; Johannes C. Paetzold; Alina Dima; Bjoern H. Menze; Benjamin Knier; Daniel Rueckert (MICCAI (8), 2022)

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Felix Steinbauer; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Martin J. Menten; et al. (ML4H@NeurIPS, 2022)

Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data. - Paul Hager; Martin J. Menten; Daniel Rueckert (CVPR, 2023)

A skeletonization algorithm for gradient-based optimization. - Martin J. Menten; Johannes C. Paetzold; Veronika A. Zimmer; Suprosanna Shit; Ivan Ezhov; Robbie Holland; Monika Probst; Julia A. Schnabel; Daniel Rueckert (ICCV, 2023)

Metrics to Quantify Global Consistency in Synthetic Medical Images. - Daniel Scholz 005; Benedikt Wiestler; Daniel Rueckert; Martin J. Menten (DGM4MICCAI, 2023)

3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images. - Alina F. Dima; Veronika A. Zimmer; Martin J. Menten; Hongwei Bran Li; Markus Graf; Tristan Lemke; Philipp Raffler; Robert Graf; Jan S. Kirschke; Rickmer Braren; Daniel Rueckert (MICCAI (1), 2023)

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. - Leonhard F. Feiner; Martin J. Menten; Kerstin Hammernik; Paul Hager; Wenqi Huang 003; Daniel Rueckert; Rickmer F. Braren; Georgios Kaissis (UNSURE@MICCAI, 2023)

Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration. - Robbie Holland; Oliver Leingang; Christopher Holmes; Philipp Anders; Rebecca Kaye; Sophie Riedl; Johannes C. Paetzold; Ivan Ezhov; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Hendrik P. N. Scholl; Sobha Sivaprasad; et al. (MICCAI (7), 2023)

Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration. - Robbie Holland; Oliver Leingang; Christopher Holmes; Philipp Anders; Johannes C. Paetzold; Rebecca Kaye; Sophie Riedl; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Lars Fritsche; Hendrik P. N. Scholl; Sobha Sivaprasad; et al. (CoRR, 2023)

Detailed retinal vessel segmentation without human annotations using simulated optical coherence tomography angiographs. - Linus Kreitner; Johannes C. Paetzold; Nikolaus Rauch; Chen Chen 042; Ahmed M. Hagag; Alaa E. Fayed; Sobha Sivaprasad; Sebastian Rausch; Julian Weichsel; Bjoern H. Menze; Matthias Harders; Benjamin Knier; et al. (CoRR, 2023)

Unlocking the Diagnostic Potential of ECG through Knowledge Transfer from Cardiac MRI. - Özgün Turgut; Philip Müller; Paul Hager; Suprosanna Shit; Sophie Starck; Martin J. Menten; Eimo Martens; Daniel Rueckert (CoRR, 2023)

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA. - Kaiyuan Yang 003; Fabio Musio; Yihui Ma; Norman Juchler; Johannes C. Paetzold; Rami Al-Maskari; Luciano Höher; Hongwei Bran Li; Ibrahim Ethem Hamamci; Anjany Sekuboyina; Suprosanna Shit; Houjing Huang; et al. (CoRR, 2023)

Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling. - Ivan Ezhov; Kevin Scibilia; Katharina Franitza; Felix Steinbauer; Suprosanna Shit; Lucas Zimmer; Jana Lipková; Florian Kofler; Johannes C. Paetzold; Luca Canalini; Diana Waldmannstetter; Martin J. Menten; et al. (Medical Image Anal., 2023)

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)

Spatiotemporal Representation Learning for Short and Long Medical Image Time Series. - Chengzhi Shen; Martin J. Menten; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Hendrik P. N. Scholl; Sobha Sivaprasad; Andrew J. Lotery; Daniel Rueckert; Paul Hager; Robbie Holland (MICCAI (11), 2024)

CLSMI2T3: 3D CLSM Vasculature Volume Reconstruction from A Single 2D Slice by Off-Focal Plane Signal Using Synthetic Data. - Yunheng Wu; Martin J. Menten; Linus Kreitner; Shuntaro Kawamura; Masahiro Oda 001; Yuichiro Hayashi; Takanori Takebe; Daniel Rueckert; Kensaku Mori (MOVI@MICCAI, 2024)

Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases. - Sophie Starck; Vasiliki Sideri-Lampretsa; Bernhard Kainz; Martin J. Menten; Tamara T. Mueller; Daniel Rueckert (CoRR, 2024)

Deep-learning-based clustering of OCT images for biomarker discovery in age-related macular degeneration (Pinnacle study report 4). - Robbie Holland; Rebecca Kaye; Ahmed M. Hagag; Oliver Leingang; Thomas R. P. Taylor; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; Hendrik P. N. Scholl; Daniel Rueckert; Andrew J. Lotery; Sobha Sivaprasad; Martin J. Menten (CoRR, 2024)

Specialist vision-language models for clinical ophthalmology. - Robbie Holland; Thomas R. P. Taylor; Christopher Holmes; Sophie Riedl; Julia Mai; Maria Patsiamanidi; Dimitra Mitsopoulou; Paul Hager; Philip Müller; Hendrik P. N. Scholl; Hrvoje Bogunovic; Ursula Schmidt-Erfurth; et al. (CoRR, 2024)

Towards Generalisable Time Series Understanding Across Domains. - Özgün Turgut; Philip Müller; Martin J. Menten; Daniel Rueckert (CoRR, 2024)

Image registration is a geometric deep learning task. - Vasiliki Sideri-Lampretsa; Nil Stolt Ansó; Martin J. Menten; Huaqi Qiu; Julian McGinnis; Daniel Rueckert (CoRR, 2024)

Metadata-enhanced contrastive learning from retinal optical coherence tomography images. - Robbie Holland; Oliver Leingang; Hrvoje Bogunovic; Sophie Riedl; Lars Fritsche; Toby Prevost; Hendrik P. N. Scholl; Ursula Schmidt-Erfurth; Sobha Sivaprasad; Andrew J. Lotery; Daniel Rueckert; Martin J. Menten (Medical Image Anal., 2024)

Synthetic Optical Coherence Tomography Angiographs for Detailed Retinal Vessel Segmentation Without Human Annotations. - Linus Kreitner; Johannes C. Paetzold; Nikolaus Rauch; Chen Chen 042; Ahmed M. Hagag; Alaa E. Fayed; Sobha Sivaprasad; Sebastian Rausch; Julian Weichsel; Bjoern H. Menze; Matthias Harders; Benjamin Knier; et al. (IEEE Trans. Medical Imaging, 2024)

A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets. - David Mildenberger; Paul Hager; Daniel Rueckert; Martin J. Menten (CVPR, 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)

Skelite: Compact Neural Networks for Efficient Iterative Skeletonization. - Luis D. Reyes Vargas; Martin J. Menten; Johannes C. Paetzold; Nassir Navab; Mohammad Farid Azampour (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)

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging. - Özgün Turgut; Philip Müller; Paul Hager; Suprosanna Shit; Sophie Starck; Martin J. Menten; Eimo Martens; Daniel Rueckert (Medical Image Anal., 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)

On Arbitrary Predictions from Equally Valid Models. - Sarah Lockfisch; Kristian Schwethelm; Martin J. Menten; Rickmer Braren; Daniel Rueckert; Alexander Ziller; Georgios Kaissis (CoRR, 2025)