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