Self-supervised multi-task representation learning for sequential medical images
Self-supervised representation learning has achieved promising results for downstream visual tasks in natural images. However, its use in the medical domain, where there is an underlying anatomical structural similarity, remains underexplored. To address this shortcoming, we propose a self-supervise...
| Автори: | , , |
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| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
Springer
2021
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