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Department of Radiology, Weill Cornell Medicine, New York, NY, USA, Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
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RegAL outperforms traditional methods by effectively integrating active and semi-supervised learning, achieving robust segmentation with minimal labeled data.
