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 (cm^3)	Volume obtained by the two readers (cm^3)	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