| Popis: |
In recent years, the number of lung cancer patients has continued to increase. In the process of detecting lung cancer, accurate segmentation of lung parenchyma plays a key role. In this paper, we proposed a method of lung parenchyma segmentation based on FPN++Mask R-CNN neural network model. The model improved original Mask R-CNN networks and optimized the structure of FPN (Feature Pyramid Networks), which is the feature extraction model of Mask R-CNN, by expanding the scale and level of FPN to fuse and extract more picture feature information from different levels. The experimental results show that compared with original Mask R-CNN models, FPN++Mask R-CNN demonstrates better segmentation results. |
