Table 1 Comparison results

(a) Comparison results for each component

 Without ResNeSt

0.923

0.825

0.776

0.781

 Without shape

0.901

0.811

0.734

0.740

 Without PAM&CAM

0.958

0.786

0.803

0.791

 Proposed U-Net

0.987

0.946

0.897

0.899

(b) Comparison results for different attention mechanisms

 With SE

0.935

0.755

0.645

0.611

 With GC

0.949

0.809

0.774

0.740

 With CBAM

0.961

0.902

0.812

0.827

 Proposed U-Net

0.987

0.946

0.897

0.899

(c) Comparison of the different backbones used in the proposed U-Net network

 ResNet34

0.935

0.665

0.398

0.423

 SEResNeXt50

0.951

0.805

0.734

0.752

 SENet-154

0.958

0.911

0.860

0.854

 ResNeSt

0.987

0.946

0.897

0.899

(d) Effect of the gate module

 Without a gate module

0.973

0.922

0.855

0.861

 With the gate module

0.987

0.946

0.897

0.899

(e) Results of comparison with existing advanced models

 DeepLabv3 [18]

0.938

0.745

0.570

0.566

 U-Net++ [36]

0.943

0.811

0.681

0.682

 U-Net+++ [37]

0.925

0.707

0.550

0.554

 GSCNN [38]

0.910

0.602

0.419

0.510

 ERFNet [39]

0.946

0.843

0.473

0.473

 ET-Net [40]

0.927

0.862

0.689

0.784

 Proposed U-Net

0.987

0.946

0.897

0.899