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通过基于隐性扩散的数据增强来解决阶级不平衡,以改善儿童胸部X射线中的疾病分类.

Sivaramakrishnan Rajaraman1, Zhaohui Liang1, Zhiyun Xue1

  • 1Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|March 26, 2025
PubMed
概括

隐性扩散模型 (LDM) 产生合成胸部X射线,以解决深度学习中的数据不平衡,用于医学图像分类. 这种增强显著改善了诊断性能,增强了模型的概括性.

关键词:
支气管肺炎是一种肺炎.胸部X射线 胸部X射线阶级不平衡 阶级不平衡深度学习是一种深度学习.潜在的扩散扩散.儿科 儿科 儿科肺炎是一种肺炎.合成数据增强 合成数据增强

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