Semi-supervised medical image segmentation method using multi-scale consistency adversarial learning

Yu-Jie Feng

doi:10.1016/j.bspc.2025.108250

2025-07-15

PRE

DOI：10.1016/j.bspc.2025.108250

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摘要

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• 构建了全面的扰动空间，以增强模型从有限标注数据中进行泛化的能力。 • 提出了多尺度上的强一致性和弱一致性正则化方法。 • 提出了自适应加权金字塔一致性损失，以促进一致的结果。 • 在ACDC和BraTS2019数据集上的大量实验表明了其优越的性能。

期刊

Biomedical Signal Processing and Control

IF:

4.9

论文数:

1.0W

被引数:

2.4W

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