8 papers · 1 filter
Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
Giang Nguyen, Raghav Mehta, Emma A. M. Stanley +4
Foundation models are increasingly used as image feature extractors for mammography, but their robustness under external domain shift remains unclear. We benchmark 15 foundation-mo…
Steering Optimisation Trajectories in Diffusion Representation Learning
Rajat Rasal, Avinash Kori, Tian Xia +1
We study why diffusion autoencoders can achieve similar image quality while learning substantially different latent structures. We trace this behaviour to optimisation dynamics; we…
Unified Multimodal Model for Brain MRI Imputation and Understanding
Zhiyun Song, Che Liu, Tian Xia +2
Multimodal large language models (MLLMs) hold great potential for medicine, as they inherit knowledge from LLM and allow multiple data modalities to be integrated, analysed and int…
Positional Segmentor-Guided Counterfactual Fine-Tuning for Spatially Localized Image Synthesis
Tian Xia, Matthew Sinclair, Andreas Schuh +8
Counterfactual image generation enables controlled data augmentation, bias mitigation, and disease modeling. However, existing methods guided by external classifiers or regressors…
Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis
Tian Xia, Matthew Sinclair, Andreas Schuh +8
Counterfactual image generation is a powerful tool for augmenting training data, de-biasing datasets, and modeling disease. Current approaches rely on external classifiers or regre…
Factored Classifier-Free Guidance
Tian Xia, Fabio De Sousa Ribeiro, Rajat R Rasal +3
Counterfactual generation aims to simulate realistic hypothetical outcomes under causal interventions. Diffusion models have emerged as a powerful tool for this task, combining DDI…