RADA achieves state-of-the-art barely-supervised 3D medical image segmentation by using a region-aware dual-encoder pre-trained on Alpha-CLIP within a triple-view training framework on LA2018, KiTS19 and LiTS datasets.
Semi-supervised semantic segmentation with cross pseudo supervision
2 Pith papers cite this work. Polarity classification is still indexing.
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CardioMix uses cardiac pattern-guided bidirectional fusion to mix labeled and unlabeled ECG data for better semi-supervised segmentation while keeping samples physiologically valid.
citing papers explorer
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RADA: Region-Aware Dual-encoder Auxiliary learning for Barely-supervised Medical Image Segmentation
RADA achieves state-of-the-art barely-supervised 3D medical image segmentation by using a region-aware dual-encoder pre-trained on Alpha-CLIP within a triple-view training framework on LA2018, KiTS19 and LiTS datasets.
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Bidirectional Fusion Guided by Cardiac Patterns for Semi-Supervised ECG Segmentation
CardioMix uses cardiac pattern-guided bidirectional fusion to mix labeled and unlabeled ECG data for better semi-supervised segmentation while keeping samples physiologically valid.