Research Article
Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention
Table 4
The classification F1 score of tissue types on colorectal cancer dataset.
| Model | TUM | STR | LYM | MUC | MUS | NOR | BAC | DEB | ADI |
| VGG19 [30] | 0.9870 | 0.9266 | 0.9773 | 0.9748 | 0.9662 | 0.9720 | 0.9586 | 0.9642 | 0.9580 | DeepTissue Net [14] | 0.9806 | 0.9413 | 0.9722 | 0.9784 | 0.9742 | 0.9806 | 0.9988 | 0.9711 | 0.9958 | EfficientNet [31] | 0.9814 | 0.9569 | 0.9827 | 0.9665 | 0.9671 | 0.9818 | 0.9982 | 0.9718 | 0.9942 | ResNet50 [29] | 0.9756 | 0.9243 | 0.9673 | 0.9852 | 0.9568 | 0.9866 | 0.9978 | 0.9729 | 0.9972 | ResNet50+bilinear pooling module | 0.9787 | 0.9502 | 0.9808 | 0.9614 | 0.9602 | 0.9869 | 0.9978 | 0.9771 | 0.9940 | ResNet50+attention module | 0.9803 | 0.9554 | 0.9810 | 0.9667 | 0.9826 | 0.9851 | 0.9974 | 0.9673 | 0.9940 | ResNet50+bilinear pooling module+attention module | 0.9860 | 0.9591 | 0.9845 | 0.9763 | 0.9693 | 0.9879 | 0.9982 | 0.9830 | 0.9966 |
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