基于多尺度通道重校准的乳腺癌病理图像分类

明涛,王丹,郭继昌,李锵

Breast cancer histopathological image classification using multi-scale channel squeeze-and-excitation model

Tao MING,Dan WANG,Ji-chang GUO,Qiang LI

表 3 所有网络的放大倍数相关的分类结果比较

Tab.3 Comparison of magnification-specific classification results of all networks

模型 40倍 100倍 200倍 400倍 Acc Pr R Acc Pr R Acc Pr R Acc Pr R ResNet18[12] 0.822 0.845 0.907 0.836 0.836 0.921 0.864 0.868 0.947 0.875 0.864 0.967 SE-ResNet18[11] 0.826 0.820 0.956 0.862 0.861 0.953 0.867 0.862 0.962 0.879 0.865 0.973 scSE-ResNet18[27] 0.805 0.808 0.941 0.836 0.845 0.935 0.870 0.866 0.962 0.824 0.837 0.918 msSE-ResNet18-2way 0.862 0.890 0.912 0.862 0.884 0.921 0.880 0.887 0.947 0.889 0.889 0.957 msSE-ResNet18-3way 0.829 0.856 0.902 0.868 0.878 0.940 0.874 0.905 0.913 0.882 0.884 0.951