Foundation Model-guided Iteratively Prompting and Pseudo-Labeling for Partially Labeled Medical Image Segmentation
Foundation Model-guided Iteratively Prompting and Pseudo-Labeling for Partially Labeled Medical Image Segmentation explores An iterative framework that leverages foundation models to generate and refine pseudo-labels for unlabeled organs in partially labeled medical images, improving segmentation performance.. Commercial viability score: 7/10 in Medical AI.
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