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. 2025 May 19;66(8):502–510. doi: 10.3349/ymj.2024.0198

Table 2. Comparison of the Results of Three U-Net-Based Models for BMs Detection and Segmentation.

Standard U-Net Modified U-Net Modified U-Net with GAN
LWS (%) 87.84 89.19 89.19
Average FPR 2.2 1.4 0.9* (p=0.024)
Patient-wise DSC 0.815 (±0.09) 0.846 (±0.06) 0.853 (±0.06)
Tumor volume range (lesion-wise DSC)
≥0.1 cc 0.724 (±0.27) 0.712 (±0.28) 0.715 (±0.28)
0.06–<0.1 cc 0.754 (±0.05) 0.761 (±0.08) 0.763 (±0.08)
0.04–<0.06 cc 0.540 (±0.34) 0.635 (±0.27) 0.674 (±0.17)
0.02–<0.04 cc 0.567 (±0.22) 0.553 (±0.20) 0.575 (±0.17)
<0.02 cc 0.515 (±0.34) 0.558 (±0.38) 0.556 (±0.37)

BM, brain metastases; GAN, generative adversarial network; LWS, lesion-wise sensitivity; FPR, false-positive rate; DSC, dice similarity coefficient.

Asterisk (*) indicates the statistical significance of differences between the modified U-Net with GAN and the standard U-Net, as determined by p-values.