Hidden
Proton Radiography — 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 |
|---|---|---|
| energy_loss | -1.4 – 4.6 | % |
| scattering | -3.5 – 11.5 | % |
| range_straggling | -2.1 – 6.9 | % |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | pCT-Former + gradient | 0.670 | 27.11 | 0.861 | 0.77 | ✓ Certified | Proton CT transformer, 2024 |
| 2 | FBP-MLP + gradient | 0.529 | 20.9 | 0.641 | 0.82 | ✓ Certified | Schulte et al., Med. Phys. 2008 |
| 3 | DROP-TVS + gradient | 0.498 | 20.07 | 0.602 | 0.78 | ✓ Certified | Penfold et al., Med. Phys. 2010 |
| 4 | ProtonNet + gradient | 0.497 | 19.92 | 0.595 | 0.8 | ✓ Certified | Proton CT DL reconstruction, 2022 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%