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基于CNN的自动细分和放射学在对比度增强超声波图像上具有可靠性,用于脏瘤

Yin Yang1, Fei Chen2, Hongmei Liang1

  • 1Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Frontiers in oncology
|June 19, 2023
PubMed
概括

卷积神经网络 (CNN) 模型,特别是UNet++,在自动分割对比增强超声波 (CEUS) 图像的瘤中表现出高准确性. 这种自动化细分对于放射性分析是可行的和可靠的.

关键词:
联合国网络 联合国网络 联合国网络自动细分自动细分自动细分与对比度增强的超声波.深度学习是一种深度学习.脏瘤 脏瘤

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