Research Article
Histopathological Tissue Segmentation of Lung Cancer with Bilinear CNN and Soft Attention
Table 2
The classification F1 score of tissue types on lung cancer dataset.
| Model | TUM | LYM | STR | NOR | VES | BRO | NEC | APC | BAC | OTH |
| ResNet50 [29] | 0.9686 | 0.9914 | 0.8687 | 0.8532 | 0.8512 | 0.9615 | 0.9668 | 0.9962 | 0.9959 | 0.7734 | VGG19 [30] | 0.9639 | 0.9913 | 0.8720 | 0.8354 | 0.8821 | 0.9545 | 0.9628 | 0.9939 | 0.9944 | 0.7219 | EfficientNet [31] | 0.9514 | 0.9789 | 0.8854 | 0.8414 | 0.8768 | 0.9533 | 0.9689 | 0.9955 | 0.9957 | 0.7326 | DeepTissue Net [14] | 0.9331 | 0.9640 | 0.8669 | 0.8635 | 0.8973 | 0.9542 | 0.9589 | 0.9967 | 0.9915 | 0.7852 | ResNet50+bilinear pooling module | 0.9698 | 0.9911 | 0.8753 | 0.8658 | 0.8736 | 0.9538 | 0.9638 | 0.9969 | 0.9936 | 0.7857 | ResNet50+attention module | 0.9712 | 0.9916 | 0.8862 | 0.8732 | 0.8954 | 0.9582 | 0.9615 | 0.9972 | 0.9931 | 0.7516 | ResNet50+bilinear pooling module+attention module | 0.9739 | 0.9911 | 0.9056 | 0.8788 | 0.9186 | 0.9586 | 0.9766 | 0.9952 | 0.9935 | 0.8025 |
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