Table 1. Performance metrics of five state-of-the-art AI algorithms on 6.25% low-count PET reconstruction.
Model | SSIMtest | PSNRtest | VIFtest | SSIMexternal | PSNRenternal | VIEexternal |
---|---|---|---|---|---|---|
EDSR | ||||||
Mean (SD) | 0.898 (0.033) | 39.7 (2.37) | 0.454 (0.048) | 0.949 (0.020) | 39.5 (1.14) | 0.466 (0.041) |
Median (Q1.Q3) | 0.908 (0.878,0.923) | 40.3 (38.6,41.3) | 0.462 (0.415,0.481) | 0.952 (0.931,0.966) | 39.8 (38.8,40.2) | 0.478 (0.432,0.501) |
EDSR-ViT | ||||||
Mean (SD) | 0.893 (0.035) | 38.7(1.83) | 0.433 (0.051) | 0.947 (0.021) | 38.4 (1.00) | 0.436 (0.042) |
Median (Q1,Q3) | 0.901 (0.864,0.921) |
38.9 (37.7, 39.9) | 0.438 (0.399,0.457) | 0.950 (0.925,0.964) | 38 5 (38.0, 38.9) | 0.449 (0.395,0.475) |
GAN | ||||||
Mean (SD) | 0.873 (0.040) | 37.4(2.14) | 0.417 (0.047) | 0.939 (0.022) | 35.7 (0.957) | 0.427 (0.039) |
Median (Q1,Q3) | 0.875 (0.845,0.912) | 37.6 (36.2, 38.6) | 0.420 (0.386, 0.445) | 0.939 (0.921,0.957) | 35.7 (35.2,36.1) | 0.435 (0.385, 0.459) |
U-net | ||||||
Mean (SD) | 0.885 (0.036) | 39.1 (2.39) | 0.442 (0.048) | 0.947 (0.020) | 39.6 (1.29) | 0.454 (0.042) |
Median (Q1,Q3) | 0.893 (0.859,0.919) | 39.5 (38.1,40.8) | 0.447 (0.410, 0.471) | 0.951 (0.928, 0.964) | 39.8 (38.7, 40.4) | 0.463 (0.413, 0.494) |
SwinIR | ||||||
Mean (SD) | 0.910 (0.029) | 39.9 (2.26) | 0.485 (0.046) | 0.950 (0.019) | 39.1 (1.08) | 0.483 (0.043) |
Median (Q1,Q3) | 0.918 (0.889, 0.934) | 40.3 (38.5,41.5) | 0.492 (0.453,0.516) | 0.952 (0.933, 0.966) | 39 3 (38.5,39.7) | 0.491 (0.443, 0.524) |
6.25% low-count PET | ||||||
Mean (SD) | 0.786 (0.047) | 35.0(2.42) | 0.263 (0.046) | 0.735 (0.030) | 34.9(1.43) | 0.257 (0.030) |
Median (Q1,Q3) | 0.802 (0.749,0.816) | 35.4 (33.4, 36.6) | 0.261 (0.234, 0.289) | 0.730 (0.711, 0.751) | 35.1 (34.3,35.1) | 0.249 (0.230, 0.282) |
All P-values, calculated using Wilcoxon signed-rank test between the Al-reconstructed PET and the low-count PET, are below 0.001