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 6 所有网络的放大倍数相关的分类结果比较

Tab.6 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 ResNet34[12] 0.846 0.880 0.898 0.859 0.887 0.912 0.874 0.901 0.918 0.882 0.888 0.946 SE-ResNet34[11] 0.849 0.870 0.917 0.863 0.887 0.916 0.877 0.894 0.933 0.886 0.888 0.951 scSE-ResNet34[27] 0.815 0.847 0.893 0.833 0.869 0.893 0.877 0.890 0.938 0.868 0.870 0.948 msSE-ResNet34-2way 0.873 0.900 0.917 0.884 0.905 0.930 0.890 0.911 0.933 0.893 0.897 0.951 msSE-ResNet34-3way 0.867 0.946 0.863 0.891 0.946 0.893 0.890 0.927 0.913 0.901 0.944 0.908