Table 2.
Summary of the submissions including processing domain, presence of coil sensitivity estimation (SE), presence of data consistency (DC), and basis of the training loss functions.
| Model | Domain | SE | DC | Loss function |
|---|---|---|---|---|
| ResoNNance 2.0 | Hybrid | Yes | Yes | MAE and SSIM |
| The Enchanted 2.0 | Hybrid | Yes | Yes | Cross entropy (pretext) and SSIM (main task) |
| ResoNNance 1.0 | Image | Yes | Yes | MAE and SSIM |
| The-Enchanted 1.0 | Image | Yes | Yes | MSE (first step) and SSIM (second step) |
| TUMRI | Hybrid | No | Yes | MS-SSIM and VIF |
| WW-Net* | Hybrid | No | Yes | MSE |
| Hybrid-cascade* | Hybrid | No | Yes | MSE |
| M-L UNICAMP | Hybrid | No | Yes | MSE |
| U-Net* | Image | No | No | MSE |
| Zero-filled* | N/A | No | N/A | N/A |
*
indicates a baseline model. Loss functions: Mean Absolute Error (MAE), Structural Similarity (SSIM), Mean Squared Error (MSE), Multi-Scale SSIM (MS-SSIM), and Visual Information Fidelity (VIF).