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Sparsely guided adaptive pseudo-supervised learning for nucleus segmentation
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DOI：10.1016/j.eswa.2026.132018.png)
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Abstract
En 中文
• A sparsely guided pseudo-supervised learning framework for nuclei segmentation. • A prior-guided feature enhancement module models nuclear boundaries. • A feature reconstruction path reconstruct and correct noisy pseudo labels under weak supervision. • A dynamic memory-aware repository stores and updates high-quality pseudo labels.
Keywords:
nuclei segmentation
pseudo-supervised learning
feature enhancement
label reconstruction
memory-aware repository
Journal
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7.5
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