Table 4 Analysis of the false positives predicted the 3D-CNN-TR model output before and after post-processing, for our private dataset (*: foramen magnum; ICA: internal carotid artery, A1: A1 segment of anterior cerebral artery, A2: A2 segment of anterior cerebral artery, ACA: anterior cerebral artery, PCA: posterior cerebral artery).

From: Automated, anatomy-based, heuristic post-processing reduces false positives and improves interpretability of deep learning intracranial aneurysm detection models

 

All FPs

FPs removed by

Method 1

Method 2

Method 3

Method 4

Method 5

Vein

53

36

49

48

49

49

Vein of Galen

12

0

12

12

12

12

Venous sinus

0

0

0

0

0

0

Cavernous venous sinus

4

0

0

0

0

0

Other intracranial veins

2

1*

2

2

2

2

Extracranial veins

35

35

35

34

35

35

Artery

97

22

22

7

30

22

Cervical artery

22

22

14

7

22

22

ICA infundibulum/branch points

37

0

1

0

1

0

MCA branch points

10

0

1

0

1

0

Caliber change at A1/A2 or ACA

5

0

1

0

1

0

Vertebrobasilar confluence

2

0

2

0

2

0

ICA occlusion

4

0

0

0

0

0

Ectatic basilar artery

1

0

0

0

0

0

Basilar tip confluence

8

0

1

0

1

0

Vertebral artery caliber change

2

0

0

0

0

0

PCA caliber change

1

0

1

0

1

0

Daughter aneurysm

1

0

0

0

0

0

Artifact (e.g. clip, calc)

4

0

1

0

1

0

Vessel

15

12

6

5

14

13

Intracranial

3

0

2

1

2

1

Extracranial

12

12

4

4

12

12

Tissue

17

8

7

6

10

10

Choroid plexus

4

0

2

2

2

2

Pineal gland

0

0

0

0

0

0

Posterior clinoid process

3

0

0

0

0

0

Other intracranial

2

0

0

0

0

0

Extracranial

8

8

5

4

8

8

Total

182

78

84

66

103

94

Intracranial

105

1

26

17

26

17

Extracranial

77

77

58

49

77

77