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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Bibliographic Details
Published in:IET image processing Vol. 18; no. 2; pp. 312 - 326
Main Authors: Xie, Junsong, Wu, Qian, Zhu, Renju
Format: Journal Article
Language:English
Published: Wiley 01.02.2024
Subjects:
ISSN:1751-9659, 1751-9667
Online Access:Get full text
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