Table 6.
Comparison of Case-PDM with other similar models from averaged human subjects data. (Correlation is between method and subjects.)
| SENSE | SPIRAL | GRAPPA | |
|---|---|---|---|
| Gray 256×256 | Gray 128×128 | Gray 209×256 | |
| Data set | Correlation coefficient (prediction accuracy) | ||
| Case-PDM | 0.944 | 0.972 | 0.914 |
| IDM | 0.955 | 0.971 | 0.958 |
| SSIM | 0.951 | 0.962 | 0.941 |
| NR | 0.824 | 0.916 | 0.930 |
| MSE | 0.712 | 0.825 | 0.891 |
| DCTune | 0.715 | 0.191 | 0.319 |
| IQM | −0.600 | −0.688 | −0.241 |
| Rank-order correlation coefficient (prediction monotonicity) | |||
| Case-PDM | 0.971 | 0.974 | 0.932 |
| IDM | 0.978 | 0.944 | 0.963 |
| SSIM | 0.974 | 0.943 | 0.958 |
| NR | 0.705 | 0.886 | 0.897 |
| MSE | 0.946 | 0.868 | 0.955 |
| DCTune | 0.815 | 0.091 | 0.459 |
| IQM | −0.166 | −0.713 | −0.074 |
| Outlier ratio (prediction consistency) | |||
| Case-PDM | 0.050 | 0.000 | 0.025 |
| IDM | 0.000 | 0.000 | 0.000 |
| SSIM | 0.025 | 0.000 | 0.000 |
| NR | 0.050 | 0.000 | 0.000 |
| MSE | 0.050 | 0.000 | 0.025 |
| DCTune | 0.050 | 0.000 | 0.000 |
| IQM | 0.075 | 0.026 | 0.050 |
| RMS error | |||
| Case-PDM | 10.643 | 5.936 | 12.869 |
| IDM | 9.637 | 6.073 | 9.081 |
| SSIM | 10.002 | 6.881 | 10.755 |
| NR | 18.364 | 10.121 | 11.608 |
| MSE | 22.735 | 14.293 | 14.410 |
| DCTune | 22.638 | 24.800 | 30.030 |
| IQM | 25.901 | 18.337 | 30.759 |