基于全卷积网络的乳腺肿瘤动态增强磁共振图像分割
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邱玥,聂生东,魏珑
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Segmentation of Breast Tumors Based on Fully Convolutional Network and Dynamic Contrast Enhanced Magnetic Resonance Image
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Yue QIU,Sheng-dong NIE,Long WEI
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表4 5种方法评价指标对比
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Table 4 Comparison of evaluation indicators of the 5 methods
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方法 | | Dice系数 | 敏感度 | 特异性 | IoU | 耗时/s | 无后处理 | 有后处理 | U-Net | | 0.9001 | 0.9057 | 0.9469 | 0.9994 | 0.8425 | 1.8931 | ResU-Net | | 0.9056 | 0.9142 | 0.9296 | 0.9988 | 0.8495 | 1.7236 | U-Net++ | | 0.9175 | 0.9198 | 0.9201 | 0.9985 | 0.8601 | 2.0370 | RAU-Net | | 0.9202 | 0.9254 | 0.9566 | 0.9990 | 0.8624 | 1.7936 | | | | | | | | | CBP5-Net+ RAU-Net | 大肿瘤 | 0.9506 | 0.9579 | 0.9580 | 0.9983 | 0.9001 | | 小肿瘤 | 0.9167 | 0.9197 | 0.9466 | 0.9988 | 0.8535 | 1.8162 | 平均 | 0.9336 | 0.9388 | 0.9523 | 0.9985 | 0.8768 | |
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