Curriculum Consistency Learning and Multi-Scale Contrastive Constraint in Semi-Supervised Medical Image Segmentation

Data scarcity poses a significant challenge in medical image segmentation, thereby highlighting the importance of leveraging sparse annotation data. In addressing this issue, semi-supervised learning has emerged as an effective approach for training neural networks using limited labeled data. In thi...

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Autori principali:	Weizhen Ding, Zhen Li
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2023-12-01
Serie:	Bioengineering
Soggetti:	medical image segmentation semi-supervised learning curriculum learning consistency loss contrastive learning
Accesso online:	https://www.mdpi.com/2306-5354/11/1/10
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