Entropy‐guided contrastive learning for semi‐supervised medical image segmentation

Accurately segmenting medical images is a critical step in clinical diagnosis and developing patient‐specific treatment plans. While supervised learning algorithms have achieved excellent performance in this area, they require a large amount of annotated data, which is often time‐consuming and diffi...

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Veröffentlicht in:	IET image processing Jg. 18; H. 2; S. 312 - 326
Hauptverfasser:	Xie, Junsong, Wu, Qian, Zhu, Renju
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Wiley 01.02.2024
Schlagworte:	contrastive learning Covid‐19 entropy‐guided medical image segmentation semi‐supervised learning
ISSN:	1751-9659, 1751-9667
Online-Zugang:	Volltext
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