Table 2.

Mean with standard deviation values of evaluation metrics using different training data size.

Training data (Number of images)	DSC (Mean ±std)	Jaccard index (Mean ±std)	Accuracy (Mean ±std)	Recall (Mean ±std)	Precision (Mean ±std)	Specificity (Mean ±std)
1,000	0.8831 ± 0.0356	0.7907 ± 0.0401	0.9457 ± 0.018	0.9681 ± 0.216	0.7937 ± 0.055	0.8057 ± 0.033
2,000	0.8945 ± 0.0365	0.8091 ± 0.0372	0.9581 ± 0.018	0.9712 ± 0.201	0.8398 ± 0.052	0.8462 ± 0.057
3,000	0.9071 ± 0.0281	0.8299 ± 0.0313	0.9703 ± 0.016	0.9809 ± 0.170	0.8730 ± 0.056	0.899 ± 0.041
4,000	0.9221 ± 0.0237	0.8555 ± 0.0294	0.9876 ± 0.015	0.9902 ± 0.165	0.9315 ± 0.049	0.9658 ± 0.040
5,000	0.9228 ± 0.0233	0.8566 ± 0.2899	0.9881 ± 0.015	0.9903 ± 0.163	0.9317 ± 0.050	0.9660 ± 0.042