The semi-supervised medical image segmentation method based on adaptive perturbation enhancement and progressive consistency propagation
Abstract Semi-supervised learning (SSL) has demonstrated strong potential in medical image segmentation by leveraging limited labeled data alongside abundant unlabeled data. However, its effectiveness is often constrained by unreliable pseudo-labels and inefficient use of unlabeled samples. To addre...
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| Asıl Yazarlar: | , , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Springer
2025-10-01
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| Seri Bilgileri: | Journal of King Saud University: Computer and Information Sciences |
| Konular: | |
| Online Erişim: | https://doi.org/10.1007/s44443-025-00265-2 |
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