Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation
Automated diagnosis from chest computed tomography (CT) scans faces two persistent challenges in clinical deployment: distribution shift across acquisition sites and performance disparity across demographic subgroups. We address both simultaneously across two complementary tasks: binary COVID-19 classification from multi-site CT volumes (Task 1) and four-class lung pathology recognition with gender-based fairness constraints (Task 2). Our framework combines a lightweight MobileViT-XXS slice encoder with a two-layer SliceTransformer aggregator for volumetric reasoning, and trains with a KL-regularised Group Distributionally Robust Optimisation (Group DRO) objective that adaptively upweight...
| Authors | Samuel Johnny, Blessed Guda, Goodness Obasi et al. |
|---|---|
| Primary category | cs.CV |
| Published | 16 March 2026 |
| Last updated at source | 27 April 2026 |
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