Table 3.
Comparison of quantitative error metrics in the retrospective test set between DNN and TSE
| DNN-N1retro | TSE-N1retro | p-value | DNN-N2retro | TSE-N2retro | p-value | |
|---|---|---|---|---|---|---|
| (DNN-N1retro
vs TSE-N1retro) |
(DNN-N2retro
vs TSE-N2retro) |
|||||
| NRMSE (%) | 7.7 ± 1.0 | 13.4 ± 2.5 | <0.001 | 5.7 ± 0.9 | 8.0 ± 1.9 | <0.001 |
| SSIM (0–1) | 0.92 ± 0.03 | 0.81 ± 0.06 | <0.001 | 0.95 ± 0.02 | 0.91 ± 0.04 | <0.001 |
| PSNR (dB) | 34.9 ± 1.5 | 30.1 ± 1.9 | <0.001 | 37.4 ± 1.7 | 34.6 ± 2.2 | <0.001 |
N represents the number of acquisitions; DNN, a deep neural network; NRMSE, normalized root mean squared error; PSNR, peak signal-to-noise-ratio; SSIM, structure similarity index; TSE, turbo-spin echo images;retro, the retrospective undersampling was applied to the data.