Hidden
DEXA — 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_offset | -0.7 – 2.3 | keV |
| soft_tissue | -2.1 – 6.9 | % |
| beam_overlap | -0.014 – 0.046 |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | SwinDXA + gradient | 0.742 | 30.46 | 0.924 | 0.84 | ✓ Certified | Liu et al., ICCV 2021 (DEXA adapt.) |
| 2 | PhysDXA + gradient | 0.728 | 29.36 | 0.907 | 0.86 | ✓ Certified | Raissi et al., J. Comput. Phys. 2019 (DEXA) |
| 3 | PnP-DXA + gradient | 0.699 | 28.35 | 0.888 | 0.8 | ✓ Certified | Venkatakrishnan et al., 2013 (DEXA adapt.) |
| 4 | DiffusionDXA + gradient | 0.693 | 28.62 | 0.893 | 0.75 | ✓ Certified | Blattmann et al., arXiv 2023 (DEXA adapt.) |
| 5 | DXA-CNN + gradient | 0.637 | 24.64 | 0.791 | 0.87 | ✓ Certified | Lee et al., Bone 2020 |
| 6 | BML-Sep + gradient | 0.618 | 24.04 | 0.77 | 0.85 | ✓ Certified | Lehmann et al., Med. Phys. 1981 |
| 7 | DXA-U-Net + gradient | 0.570 | 22.84 | 0.725 | 0.76 | ✓ Certified | Huo et al., IEEE TMED 2021 |
| 8 | FBP-DEXA + gradient | 0.568 | 22.06 | 0.693 | 0.85 | ✓ Certified | Mazess et al., Am. J. Clin. Nutr. 1990 |
| 9 | TV-DEXA + gradient | 0.565 | 21.81 | 0.682 | 0.87 | ✓ Certified | Sidky & Pan, Phys. Med. Biol. 2008 (DEXA) |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%