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Found 3 papers, 2 papers with code
CineMA: A Foundation Model for Cine Cardiac MRI
CineMA is the first foundation model for cine CMR to match or outperform convolutional neural networks (CNNs).
T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging
Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater accuracy improvement.
Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training.
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