Boundary-Aware Prototype in Semi-Supervised Medical Image Segmentation
The true label plays an important role in semi-supervised medical image segmentation (SSMIS) because it can provide the most accurate supervision information when the label is limited. The popular SSMIS method trains labeled and unlabeled data separately, and the unlabeled data cannot be directly su...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 33(2024) vom: 01., Seite 5456-5467 |
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| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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