Hidden
PET/MR — Hidden Tier
(3 scenes)Fully blind server-side evaluation — no data download.
What you get
No data downloadable. Algorithm runs server-side on hidden measurements.
How to use
Package algorithm as Docker container / Python script. Submit via link.
What to submit
Containerized algorithm accepting y + H, outputting x_hat + corrected spec.
Parameter Specifications
🔒
True spec hidden — blind evaluation, only ranges available.
| Parameter | Spec Range | Unit |
|---|---|---|
| mr_attenuation_error | -17.5 – 57.5 | % |
| motion_shift | -4.2 – 13.8 | pixels |
| b0_inhomogeneity | -28.0 – 92.0 | Hz |
| pet_scatter_fraction | -0.175 – 0.575 |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PET-ViT + gradient | 0.717 | 29.63 | 0.911 | 0.78 | ✓ Certified | Smith et al., ICCV 2024 |
| 2 | PETFormer + gradient | 0.682 | 27.57 | 0.871 | 0.79 | ✓ Certified | Li et al., ECCV 2024 |
| 3 | FBP-PET + gradient | 0.666 | 27.16 | 0.862 | 0.75 | ✓ Certified | Analytical baseline |
| 4 | TransEM + gradient | 0.661 | 25.83 | 0.827 | 0.86 | ✓ Certified | Xie et al., 2023 |
| 5 | U-Net-PET + gradient | 0.653 | 25.93 | 0.83 | 0.81 | ✓ Certified | Ronneberger et al. variant, MICCAI 2020 |
| 6 | ML-EM + gradient | 0.628 | 25.24 | 0.81 | 0.76 | ✓ Certified | Shepp & Vardi, IEEE TPAMI 1982 |
| 7 | OS-EM + gradient | 0.596 | 23.85 | 0.763 | 0.76 | ✓ Certified | Hudson & Larkin, IEEE TMI 1994 |
| 8 | OSEM + gradient | 0.564 | 22.23 | 0.7 | 0.81 | ✓ Certified | Hudson & Larkin, IEEE TMI 1994 |
| 9 | DeepPET + gradient | 0.524 | 20.55 | 0.625 | 0.84 | ✓ Certified | Haggstrom et al., MIA 2019 |
| 10 | MAPEM-RDP + gradient | 0.469 | 19.31 | 0.565 | 0.75 | ✓ Certified | Nuyts et al., IEEE TMI 2002 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%