Rethinking semi-supervised medical image segmentation: a variance-reduction perspective
For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. This is enabled by the observation that without accessing ground truth labels, negative examples with tr...
| Main Authors: | , , , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Curran Associates
2023
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