82 citations · 84 across the 4 of their papers we have counts for
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cs.CV2024
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
Richard Osuala, Daniel M. Lang, Anneliese Riess +6
Deep learning holds immense promise for aiding radiologists in breast cancer detection. However, achieving optimal model performance is hampered by limitations in availability and…
eess.IV2024★ 1 cited
Fairness-Aware Data Augmentation for Cardiac MRI using Text-Conditioned Diffusion Models
Grzegorz Skorupko, Richard Osuala, Zuzanna Szafranowska +6
While deep learning holds great promise for disease diagnosis and prognosis in cardiac magnetic resonance imaging, its progress is often constrained by highly imbalanced and biased…