Appendix 1—table 4. Ablation study of each module of BEN in the source domain.

(a) training with all labeled data using U-Net. The backbone of BEN is non-local U-Net (NL-U-Net). (b) training with 5% labeled data. (c) training with 5% labeled data using BEN’s semi-supervised learning module (SSL). The remaining 95% of the unlabeled data is also used for the training. Since this ablation study is performed on the source domain, the adaptive batch normalization (AdaBN) module is not used. Dice: Dice score; SEN: sensitivity; SPE: specificity; HD95: the 95-th percentile of Hausdorff distance.

Method	Scans used		Metrics
	Labeled	Unlabeled	Dice	SEN	SPE	HD95
aU-Net	243	0	0.9773	0.9696	0.9984	0.2132
aBackbone	243	0	0.9844	0.9830	0.9984	0.0958
bU-Net	12	0	0.9588	0.9546	0.9945	1.1388
bBackbone	12	0	0.9614	0.9679	0.9970	0.7468
cBackbone +SSL	12	231	0.9728	0.9875	0.9952	0.2937