U-Net Based Feature Interaction Segmentation Method
SUN Junding1,2, HUI Zhenkun1, TANG Chaosheng1, WU Xiaosheng1,2
1. College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000
2. Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou 215006
To address the problems of mis-segmentation and missing segmentation of small targets in liver segmentation, a U-Net based feature interaction segmentation method is proposed using ResNet34 as the backbone network. To achieve non-local interactions between different scales, a transformer-based feature interaction pyramid module is designed as the bridge of the network to obtain feature maps with richer contextual information. A multi-scale attention mechanism is designed to replace the jumping connection in U-Net, considering the small targets in the image and sufficiently acquiring the contextual information of the target layer. Experiments on the public dataset LiTS and the dataset consisting of 3Dircadb and CHAOS demonstrate that the proposed method achieves good segmentation results.
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2021, Vol. 34 
