Table 2.
Top 10 algorithms with the best scores in each category evaluated for the QSM reconstruction challenge.
| RMSE (%) | HFEN (%) | SSIM | ROI ERROR (ppm) | ||||
|---|---|---|---|---|---|---|---|
| 69.0 | VANC UBC | 63.5 | JHU-XMU SFCR2 | 0.94 | JHU-XMU SFCR2 | 0.016 | SMU MATV |
| 70.3 | JHU-XMU SFCR2 | 68.8 | GRAZ TGV L1 | JHU-XMU SFCRKDN | NY PD | ||
| 73.6 | MARTINOS WTV | 68.9 | VANC UBC | 0.93 | NY MEDI | 0.017 | CHILE TGV NL |
| 74.2 | PHILIPS DTV | 70.9 | PHILIPS DTV | GRAZ TGV | CHILE NLD | ||
| 74.6 | GRAZ TGV L1 | 71.8 | SMU MATV | 0.87 | GRAZ TGV L1 | SMU MTKD | |
| 75.2 | UCL TIK 1 | 73.1 | UCL TIK 1 | 0.84 | CHILE TGV L2 | 0.018 | CFL2 |
| 76.6 | UCL TKD 1 | 73.6 | MARTINOS WTV | NY TFI | UCL TIK 2 | ||
| 77.5 | GRAZ TGV | 74.1 | IBR ITSWIM | 0.83 | JENA HEIDI | UCL TIK 4 | |
| BERKELEY STAR | 74.2 | JHU-XMU SFCRKDN | CHILE NLD | JHU-XMU SFCRKDN | |||
| 79.1 | SMU MATV | GRAZ TGV | CHILE TGV NL | CHILE TGV L2 | |||