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...
Huvudupphovsmän: | , , , , , , , , |
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Materialtyp: | Conference item |
Språk: | English |
Publicerad: |
IEEE
2022
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