375 citations · 878 across the 24 of their papers we have counts for
4 papers · 1 filter
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations
Lidia Garrucho, Kaisar Kushibar, Claire-Anne Reidel +30
Artificial Intelligence (AI) research in breast cancer Magnetic Resonance Imaging (MRI) faces challenges due to limited expert-labeled segmentations. To address this, we present a…
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…
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models
Richard Osuala, Daniel M. Lang, Preeti Verma +9
Contrast agents in dynamic contrast enhanced magnetic resonance imaging allow to localize tumors and observe their contrast kinetics, which is essential for cancer characterization…