Dev
Electron Tomo — Dev Tier
(3 scenes)Blind evaluation tier — no ground truth available.
What you get
Measurements (y), ideal forward operator (H), and spec ranges only.
How to use
Apply your pipeline from the Public tier. Use consistency as self-check.
What to submit
Reconstructed signals and corrected spec. Scored server-side.
Parameter Specifications
🔒
True spec hidden — estimate parameters from spec ranges below.
| Parameter | Spec Range | Unit |
|---|---|---|
| tilt_angle | -0.6 – 0.9 | deg |
| tilt_axis | -0.36 – 0.54 | deg |
| defocus_gradient | -12.0 – 18.0 | nm/μm |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | SwinET + gradient | 0.754 | 30.95 | 0.93 | 0.86 | ✓ Certified | Wang et al., Ultramicroscopy 2023 |
| 2 | DiffET + gradient | 0.753 | 31.33 | 0.935 | 0.83 | ✓ Certified | Gao et al., NeurIPS 2024 |
| 3 | TransET + gradient | 0.715 | 28.69 | 0.895 | 0.85 | ✓ Certified | Li et al., Nat. Methods 2022 |
| 4 | PhysET + gradient | 0.685 | 26.79 | 0.853 | 0.88 | ✓ Certified | Chen et al., Nat. Commun. 2024 |
| 5 | IsoNet + gradient | 0.624 | 24.11 | 0.772 | 0.87 | ✓ Certified | Liu et al., Nat. Commun. 2021 |
| 6 | DnCNN-ET + gradient | 0.587 | 22.47 | 0.71 | 0.89 | ✓ Certified | Buchholz et al., Nat. Methods 2019 |
| 7 | SIRT-ET + gradient | 0.562 | 21.91 | 0.686 | 0.84 | ✓ Certified | Gilbert, J. Theor. Biol. 1972 |
| 8 | WBP-ET + gradient | 0.410 | 17.12 | 0.456 | 0.78 | ✓ Certified | Radermacher et al., J. Microsc. 1987 |
| 9 | CS-ET + gradient | 0.409 | 16.9 | 0.445 | 0.81 | ✓ Certified | Leary et al., Ultramicroscopy 2013 |
Visible Data Fields
y
H_ideal
spec_ranges
Dataset
Format: HDF5
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%