Researchers develop collaborative framework using unlabeled data for enhanced semi-supervised MRI segmentation

Researchers from Peking University Third Hospital have developed a novel collaborative framework that integrates various semi-supervised learning techniques to enhance MRI segmentation using unlabeled data. This new approach, published in Health Data Science, leverages advanced deep learning models to significantly improve segmentation accuracy, even when labeled data is scarce.

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