Table 2.
Effect of different training data volumes on segmentation performance
| Subset Name | High Resolution | Low Resolution | Total Images | Dice (%) |
|---|---|---|---|---|
| imagenet | 0 | 0 | 0 | 67.94 ± 1.15 |
| subset_highres_only | 6,259 | 0 | 6,259 | 68.78 ± 1.05 |
| subset_lowres_10k | 0 | 10,000 | 10,000 | 70.40 ± 1.32 |
| subset_lowres_20k | 0 | 20,000 | 20,000 | 71.06 ± 0.90 |
| subset_lowres_30k | 0 | 30,000 | 30,000 | 71.15 ± 0.88 |
| subset_lowres_40k | 0 | 40,000 | 40,000 | 71.39 ± 0.85 |
| subset_lowres_50k | 0 | 50,000 | 50,000 | 71.71 ± 0.84 |
| subset_lowres_60k | 0 | 60,000 | 60,000 | 72.00 ± 0.75 |
| All_data | 6,259 | 68,033 | 74,292 | 73.17 ± 0.95 |