SAA-Net: U-shaped network with Scale-Axis-Attention for liver tumor segmentation

Chi Zhang, Jingben Lu, Qianqian Hua, Chunguo Li, Pengwei Wang

Abstract: Highlights•We propose the Scale Attention mechanism, which is effective for multi-scale problem in liver tumor segmentation.•We improve the self-attention and propose the Axis Attention mechanism, which is efficient and effective for spatial information modeling globally.•We combine the Scale Attention and the Axis Attention mechanisms organically with a style of adaptive global pooling in SAA-Net, which is efficient for preserving fine-grained information in global pooling, beneficial to final segmentation.