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SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation
In the era of information explosion, efficiently leveraging large-scale unlabeled data while minimizing the reliance on high-quality pixel-level annotations remains a critical challenge in the field of medical imaging. Semi-supervised learning (SSL) enhances the utilization of unlabeled data by faci
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