Appendix 1—table 5. Ablation study of each module of BEN in the target domain.
(a) training from scratch with all labeled data. The backbone of BEN is non-local U-Net (NL-U-Net). (b) training from scratch with 5% labeled data. (c) fine-tuning (using pretrained weights) with 5% labeled data. (d) fine-tuning with 5% labeled data using BEN’s SSL and AdaBN modules. The remaining 95% of the unlabeled data is also used for the training stage. Dice: Dice score; SEN: sensitivity; SPE: specificity; HD95: the 95-th percentile of Hausdorff distance.
| Method | Pretrained | Scans used | Metrics | ||||
|---|---|---|---|---|---|---|---|
| Labeled | Unlabeled | Dice | SEN | SPE | HD95 | ||
|
aBackbone (from scratch) |
132 | 0 | 0.9827 | 0.9841 | 0.9987 | 0.1881 | |
|
bBackbone (from scratch) |
7 | 0 | 0.8990 | 0.8654 | 0.9960 | 4.6241 | |
| cBackbone | ✓ | 7 | 0 | 0.9483 | 0.9063 | 0.9997 | 0.6563 |
| cBackbone +AdaBN | ✓ | 7 | 0 | 0.9728 | 0.9875 | 0.9952 | 0.2937 |
| dBackbone +SSL | ✓ | 7 | 125 | 0.9614 | 0.9679 | 0.9970 | 0.7468 |
| dBackbone +AdaBN + SSL | ✓ | 7 | 125 | 0.9779 | 0.9763 | 0.9986 | 0.2912 |