Publications (160)
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Meritxell Riera-Marin, Sikha O K, Julia Rodriguez-Comas +29
Deep learning (DL) has become the dominant approach for medical image segmentation, yet ensuring the reliability and clinical applicability of these models requires addressing key…
Small Organ Segmentation in Whole-body MRI using a Two-stage FCN and Weighting Schemes
Vanya V. Valindria, Ioannis Lavdas, Juan Cerrolaza +4
Accurate and robust segmentation of small organs in whole-body MRI is difficult due to anatomical variation and class imbalance. Recent deep network based approaches have demonstra…
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker +1
Despite the constant development of new bias mitigation methods for machine learning, no method consistently succeeds, and a fundamental question remains unanswered: when and why d…
Counterfactual Stress Testing for Image Classification Models
Moritz Stammel, Fabio De Sousa Ribeiro, Raghav Mehta +2
Deep learning models in medical imaging often fail when deployed in new clinical environments due to distribution shifts in demographics, scanner hardware, or acquisition protocols…
A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
Charles Jones, Ben Glocker
Machine learning methods often fail when deployed in the real world. Worse still, they fail in high-stakes situations and across socially sensitive lines. These issues have a chill…
Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
Zeju Li, Konstantinos Kamnitsas, Ben Glocker
Overfitting in deep learning has been the focus of a number of recent works, yet its exact impact on the behavior of neural networks is not well understood. This study analyzes ove…