469 citations · 706 across the 59 of their papers we have counts for
15 papers · 2 filters
A Data-Interventional Framework for Auditing Privacy and Fairness in Generative Medical Imaging
Mischa Dombrowski, Bernhard Kainz
Diffusion-based synthetic data generation offers a promising route for sharing medical imaging data without releasing sensitive patient records. However, generative models face a f…
MMAP: Multimodal Missing-Aware Pretraining for Longitudinal Alzheimer's Prediction
Fiona Kekwick, Matthew Baugh, Bernhard Kainz +2
Clinical decision making heavily relies on predicting the disease progression trajectory by seeking to understand patient's health status which is characterised by multimodal medic…
A Principled Approach to Unsupervised Anomaly Detection
James Myles, Matthew Baugh, Johanna P. Müller +2
Traditional unsupervised anomaly detection (UAD) methods are designed to flag or localise deviations from a normative distribution, ignoring the underlying generative mechanisms of…
Self-Supervised Cardiac Phase Detection via Single-Parameter Latent Orbits
John Bonnici, Matthew Baugh, Aleksandra Kulbaka +3
Accurate identification of end-diastole (ED) and end-systole (ES) in echocardiography underpins the quantification of ventricular function, yet manual selection of these key frames…
Frozen DINO Localizes Image Edits Without a Localizer
Zane Kumar, Vishal Jain, Bernhard Kainz
Localized image edits can change a photograph's meaning while leaving most of it authentic, so forensic analysis must identify where an edit occurred. We show that patch-level pert…
Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging
Bernhard Kainz, Johanna P Mueller, Matthew Baugh +1
Zero-shot anomaly localisation via vision-language models (VLMs) offers a compelling approach for rare pathology detection, yet its performance is fundamentally limited by the abse…