Hidden
Optical Diffraction Tomography (ODT) — Hidden Tier
(5 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 |
|---|---|---|
| illumination_angle_error | -0.28 – 0.92 | degperangle |
| missing_cone_artifact | 27.2 – 39.2 | deg |
| refractive_index_of_medium | 1.33518 – 1.34298 | - |
| multiple_scattering | -1.4 – 4.6 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | Rytov-Former + gradient | 0.641 | 25.89 | 0.829 | 0.75 | ✓ Certified | ODT reconstruction transformer, 2024 |
| 2 | ODT-Net + gradient | 0.598 | 23.22 | 0.74 | 0.85 | ✓ Certified | Zhou et al., Light: S&A 2023 |
| 3 | Born-ADMM + gradient | 0.571 | 22.85 | 0.725 | 0.76 | ✓ Certified | Lim et al., Phys. Rev. Lett. 2015 |
| 4 | Wolf FBP + gradient | 0.518 | 20.49 | 0.622 | 0.82 | ✓ Certified | Wolf, Opt. Commun. 1969 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%