Tumor Segmentation in Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma: Deep Learning with Convolutional Neural Network
Table 2
The segmentation performance of all cases.
Patients number
Volume of current DL method (cm3)
Volume obtained by the two readers (cm3)
Percent match
Corresponding ratio
Dice similarity coefficient
Recall
Jaccard similarity coefficient
1
7.8
8.0
0.84
0.74
0.83
0.81
0.70
2
5.2
6.2
0.90
0.76
0.82
0.75
0.70
3
5.1
6.4
0.89
0.72
0.80
0.72
0.66
4
18.5
18.4
0.88
0.83
0.89
0.89
0.79
5
7.0
6.5
0.86
0.82
0.89
0.92
0.80
6
11.9
10.6
0.85
0.82
0.89
0.94
0.81
7
11.9
11.9
0.83
0.74
0.83
0.82
0.71
8
11.0
10.2
0.85
0.82
0.89
0.92
0.80
9
5.9
6.7
0.90
0.78
0.84
0.79
0.73
10
14.8
17.1
0.86
0.71
0.80
0.75
0.66
11
4.4
4.7
0.96
0.91
0.93
0.91
0.87
12
17.3
17.9
0.94
0.89
0.92
0.90
0.85
13
4.5
4.3
0.88
0.84
0.90
0.92
0.82
14
46.7
45.0
0.93
0.91
0.95
0.97
0.90
15
5.8
5.7
0.88
0.82
0.88
0.89
0.79
16
8.8
9.2
0.90
0.83
0.88
0.87
0.79
17
5.7
6.8
0.92
0.79
0.84
0.78
0.73
18
10.7
11.2
0.94
0.89
0.92
0.90
0.85
19
10.6
10.9
0.95
0.91
0.94
0.93
0.88
20
8.6
8.9
0.93
0.88
0.91
0.90
0.84
21
13.3
13.9
0.93
0.87
0.91
0.89
0.83
22
13.7
13.6
0.95
0.92
0.95
0.95
0.90
23
6.3
6.5
0.90
0.83
0.88
0.87
0.79
24
16.2
16.5
0.95
0.92
0.94
0.94
0.89
25
18.2
17.7
0.94
0.92
0.95
0.96
0.91
26
11.4
11.1
0.91
0.87
0.92
0.93
0.85
27
10.8
11.0
0.88
0.80
0.87
0.86
0.76
28
17.1
17.9
0.95
0.90
0.93
0.91
0.86
29
12.0
12.2
0.94
0.90
0.93
0.92
0.87
Mean±Std
-
-
0.90±0.04
0.84±0.06
0.89±0.05
0.88 ±0.07
0.81 ±0.07
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