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Table 3 Quantitative measurements between automated segmentation and manual annotation

From: Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study

Quantitative metrics

All LNs

Suspicious LNs

Largest LNs

 

Automated segmentation

Manual annotation

P

Automated segmentation

Manual annotation

P value

Automated segmentation

Manual annotation

P value

Internal test dataset

         

Volume (mm3)

172.3 [71.1, 390.3]

197.9 [83.0, 449.2]

0.002

623.0 [374.3, 1123.1]

785.1 [517.9, 1389.3]

0.000

10.3 [8.7, 13.8]

10.8 [9.4, 15.1]

0.000

Short diameter (mm)

5.4 [3.9,7.3]

5.7 [4.0,7.7]

0.000

9.1 [7.7, 11.2]

9.7 [8.7, 11.9]

0.000

752.3 [466.4, 1548.5]

886.2 [530.8, 1787.2]

0.000

External validation dataset

         

Volume (mm3)

103.3 [45.9, 244.90]

130.3 [61.2, 304.2]

0.000

428.6 [244.9, 688.8]

551.0 [382.7, 870.9]

0.000

212.2 [95.1, 382.6]

266.0 [134.7, 463.2]

0.000

Short diameter (mm)

4.8 [3.4, 6.9]

5.1 [3.6, 7.5]

0.000

8.7 [7.4, 10.1]

9.4 [8.6, 10.7]

0.000

6.3 [4.7, 8.1]

6.8 [5.0, 8.6]

0.000

  1. LNs lymph nodes