融合多尺度和多头注意力的医疗图像分割方法

王万良,王铁军,陈嘉诚,尤文波

Medical image segmentation method combining multi-scale and multi-head attention

Wan-liang WANG,Tie-jun WANG,Jia-cheng CHEN,Wen-bo YOU

表 9 不同算法在ISBI 2017数据集上的分割性能对比

Tab.9 Comparison of segmentation performance of different algorithms on ISBI 2017 dataset

% 方法 JA DI ACC SEN SPE TJI U-Net 72.81 81.78 92.23 80.36 97.33 60.83 Attention U-Net 72.93 81.89 92.10 81.72 96.97 61.27 Swin-Unet 66.04 75.61 90.46 79.11 93.81 52.58 RAUNet 77.26 85.49 93.68 83.48 97.50 69.47 SFUNet 76.15 84.57 93.38 82.98 96.83 67.01 DeepLab v3+ (Xception) 77.37 85.67 93.61 83.96 96.90 69.10 CE-Net 77.46 85.43 93.68 83.84 97.12 70.49 CA-Net 77.16 85.38 93.13 85.80 95.53 68.56 UTNet 77.47 85.51 93.55 87.15 95.48 70.10 MS-Dual-Guided 76.48 84.72 92.65 87.11 94.54 68.17 MS2Net 78.43 86.28 93.81 85.96 96.72 71.60