FEW-SHOT image segmentation for cross-institution male pelvic organs using registration-assisted prototypical learning
The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class are available from local healthcare providers, is sought-after. This potentially addresses two widely recognised limitati...
| Автори: | , , , , , , , , |
|---|---|
| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
IEEE
2022
|