1 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
Efficient Semantic Diffusion Architectures for Model Training on Synthetic Echocardiograms
David Stojanovski, Mariana da Silva, Pablo Lamata +2
We investigate the utility of diffusion generative models to efficiently synthesise datasets that effectively train deep learning models for image analysis. Specifically, we propos…
Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography
Kit M. Bransby, Woo-jin Cho Kim, Jorge Oliveira +4
Building an echocardiography view classifier that maintains performance in real-life cases requires diverse multi-site data, and frequent updates with newly available data to mitig…
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation
Jack Highton, Quok Zong Chong, Samuel Finestone +3
Deep learning models for medical image segmentation and object detection are becoming increasingly available as clinical products. However, as details are rarely provided about the…
BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision
Kit Mills Bransby, Arian Beqiri, Woo-Jin Cho Kim +3
Neural networks can learn spurious correlations that lead to the correct prediction in a validation set, but generalise poorly because the predictions are right for the wrong reaso…