RL4Seg3D applies reinforcement learning with novel reward functions and fusion to adapt echocardiography segmentation models across domains, improving accuracy, anatomical validity, and temporal consistency on over 30,000 videos without target labels.
Simple and scal- able predictive uncertainty estimation using deep ensembles,
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Reinforcement Learning for Unsupervised Domain Adaptation in Spatio-Temporal Echocardiography Segmentation
RL4Seg3D applies reinforcement learning with novel reward functions and fusion to adapt echocardiography segmentation models across domains, improving accuracy, anatomical validity, and temporal consistency on over 30,000 videos without target labels.