Semi-supervised medical image segmentation framework based on multi-perturbation Mean Teacher model
In semi-supervised medical image segmentation， consistency regularization is widely regarded as an effective approach. This approach applies various perturbations to feature maps and， through a consistency constraint， guides the model to learn essential features from the perturbed outputs during tra...
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| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Editorial Department of Journal of Sichuan University (Natural Science Edition)
2026-01-01
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| Серія: | 四川大学学报. 自然科学版 |
| Предмети: | |
| Онлайн доступ: | http://science.scu.edu.cn/thesisDetails#10.19907/j.0490-6756.250148 |
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