融合注意力机制和空洞卷积的3D ELD_MobileNetV2在肝结节分类中的应用

孙灏芸, 王丽嘉

Application of 3D ELD_MobileNetV2 Incorporating Attention Mechanism and Dilated Convolution in Hepatic Nodules Classification

SUN Haoyun, WANG Lijia

表4 不同网络模型的分类性能比较

Table 4 Comparison of classification performance across different models

AlexNet VggNet16 ResNet50 ConvNeXt ELD_MobileNetV2 C0 Precision 0.483 0.588 0.647 0.714 0.786 Recall 0.778 0.556 0.611 0.556 0.611 F1_Score 0.596 0.571 0.629 0.625 0.688 C1 Precision 0.667 0.647 0.600 0.640 0.682 Recall 0.667 0.611 0.667 0.889 0.833 F1_Score 0.667 0.629 0.632 0.744 0.750 C2 Precision 0.667 0.667 0.750 0.857 0.933 Recall 0.556 0.778 0.667 0.667 0.778 F1_Score 0.606 0.718 0.706 0.750 0.848 C3 Precision 0.900 0.824 0.789 0.842 0.810 Recall 0.500 0.778 0.833 0.889 0.944 F1_Score 0.643 0.800 0.811 0.865 0.872 总体 Precision 0.679 0.682 0.697 0.763 0.803 Recall 0.625 0.681 0.695 0.750 0.792 F1_Score 0.651 0.681 0.695 0.757 0.797 Accuracy 0.625 0.681 0.694 0.750 0.792