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School of Computer Science and Technology, Tongji University, Shanghai, 201804, China
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Achieving precise medical image segmentation with limited labeled data is now possible by embracing intra-class heterogeneity through innovative prototype learning.
Prefix Retention Optimization boosts target identifier retention in multimodal generative retrieval, closing the critical indexing-decoding gap.
Overcome the limitations of existing semi-supervised segmentation methods by learning structural consensus across samples, achieving more generalizable pancreas segmentation under sparse supervision.
