Combining contrastive learning and shape awareness for semi-supervised medical image segmentation

For computer-aided diagnosis(CAD) to be successful, automatic segmentation needs to be reliable and efficient. Semi-supervised segmentation (SSL) techniques make extensive use of unlabeled data to address the issue of the high acquisition cost of medically labeled data. However, different anatomical...

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Bibliographic Details

Published in:	Expert systems with applications Vol. 242; p. 122567
Main Authors:	Chen, Yaqi, Chen, Faquan, Huang, Chenxi
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 15.05.2024
Subjects:	Contrastive learning Local boundary constraints Medical image segmentation Semi-supervised learning Semi-supervised learning Local boundary constraints Medical image segmentation Contrastive learning
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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