Hidden
Focused Ion Beam SEM (FIB-SEM) — 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 |
|---|---|---|
| slice_thickness_variation | -2.1 – 6.9 | - |
| curtaining_artifact | -0.042 – 0.138 | relative |
| charging | -42.0 – 138.0 | V |
| drift_between_slices | -0.7 – 2.3 | nm |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PhysFIB + gradient | 0.746 | 31.26 | 0.934 | 0.8 | ✓ Certified | Chen et al., Nat. Commun. 2024 |
| 2 | DiffFIB + gradient | 0.731 | 30.9 | 0.93 | 0.75 | ✓ Certified | Gao et al., NeurIPS 2024 |
| 3 | SwinFIB + gradient | 0.703 | 29.06 | 0.901 | 0.76 | ✓ Certified | Wang et al., Nat. Commun. 2023 |
| 4 | TransFIB + gradient | 0.679 | 27.7 | 0.874 | 0.76 | ✓ Certified | Li et al., Nat. Methods 2022 |
| 5 | BM3D-FIB + gradient | 0.603 | 23.65 | 0.756 | 0.82 | ✓ Certified | Dabov et al., IEEE TIP 2007 |
| 6 | DnCNN-FIB + gradient | 0.579 | 22.63 | 0.716 | 0.83 | ✓ Certified | Buchholz et al., Nat. Methods 2019 |
| 7 | NLM-FIB + gradient | 0.551 | 21.97 | 0.689 | 0.78 | ✓ Certified | Buades et al., CVPR 2005 |
| 8 | TV-FIB + gradient | 0.533 | 20.95 | 0.643 | 0.83 | ✓ Certified | Rudin et al., Physica D 1992 |
| 9 | N2V-FIB + gradient | 0.489 | 19.44 | 0.572 | 0.83 | ✓ Certified | Krull et al., NeurIPS 2019 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%