Table 2 Quantitative comparison including IoU, HD, mAP and F1 in three datasets.

From: Boundary guidance network for medical image segmentation

 

U-Net

PraNet

CaraNet

HarDNet

CENet

DCRNet

CTO

XBound

H2Former

Ours

BUSI

IoU\(\uparrow \)

0.785

0.824

0.828

0.826

0.819

0.799

0.813

0.811

0.796

0.846

HD\(\downarrow \)

8.71

8.23

8.05

8.23

8.16

8.34

8.49

8.60

8.58

7.78

mAP\(\uparrow \)

0.646

0.709

0.716

0.712

0.695

0.675

0.696

0.687

0.664

0.746

F1\(\uparrow \)

0.842

0.873

0.876

0.879

0.867

0.856

0.864

0.874

0.848

0.896

ISIC 2017

IoU\(\uparrow \)

0.821

0.842

0.823

0.848

0.811

0.829

0.843

0.848

0.856

0.862

HD\(\downarrow \)

16.51

15.84

16.73

15.78

16.10

16.19

15.81

15.48

15.48

15.39

mAP\(\uparrow \)

0.829

0.828

0.799

0.832

0.783

0.814

0.827

0.832

0.842

0.856

F1\(\uparrow \)

0.891

0.906

0.894

0.904

0.881

0.885

0.906

0.906

0.905

0.917

X-ray

IoU\(\uparrow \)

0.937

0.941

0.940

0.941

0.940

0.942

0.942

0.946

0.946

0.949

HD\(\downarrow \)

15.70

14.89

15.00

14.94

15.36

15.44

14.90

14.94

14.41

14.31

mAP\(\uparrow \)

0.922

0.925

0.921

0.928

0.907

0.912

0.928

0.928

0.927

0.936

F1\(\uparrow \)

0.966

0.965

0.968

0.969

0.961

0.960

0.966

0.972

0.973

0.973

  1. \(\uparrow \) and \(\downarrow \) denote larger and smaller is better, respectively. The italic represents the best results, bold represents the second best results.