Public
Cryo-Electron Tomography (Cryo-ET) — Public Tier
(3 scenes)Full-access development tier with all data visible.
What you get
Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.
How to use
Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.
What to submit
Reconstructed signals (x_hat) and corrected spec as HDF5.
Parameter Specifications
✓
True spec visible — use these exact values for Scenario III oracle reconstruction.
| Parameter | Spec Range | True Value | Unit |
|---|---|---|---|
| tilt_axis_offset | -0.6 – 1.2 | 0.3 | px |
| tilt_angle_accuracy | -0.2 – 0.4 | 0.1 | degpertilt |
| dose_induced_shrinkage | -2.0 – 4.0 | 1.0 | - |
| ctf_per_tilt_variation | -0.15 – 0.15 | 0.0 | um |
| missing_wedge | 26.0 – 38.0 | 32.0 | deg |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
16.13 dB
SSIM 0.1412
Scenario II (Mismatch)
15.22 dB
SSIM 0.0585
Scenario III (Oracle)
17.89 dB
SSIM 0.1644
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 15.51 | 0.1325 | 14.87 | 0.0590 | 18.06 | 0.1887 |
| scene_01 | 16.91 | 0.1523 | 15.44 | 0.0596 | 17.59 | 0.1508 |
| scene_02 | 16.78 | 0.1493 | 15.80 | 0.0608 | 18.12 | 0.1528 |
| scene_03 | 15.33 | 0.1308 | 14.76 | 0.0544 | 17.78 | 0.1653 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffusionET + gradient | 0.842 | 36.21 | 0.974 | 0.95 | ✓ Certified | Zhang et al., arXiv 2024 |
| 2 | ETFormer + gradient | 0.813 | 34.05 | 0.961 | 0.94 | ✓ Certified | Chen et al., CVPR 2024 |
| 3 | DeePiCt + gradient | 0.796 | 33.05 | 0.953 | 0.92 | ✓ Certified | Moebel et al., Nat. Methods 2021 |
| 4 | CryoSeg + gradient | 0.757 | 30.92 | 0.93 | 0.88 | ✓ Certified | Lamm et al., Nat. Methods 2022 |
| 5 | DeepDeWedge + gradient | 0.756 | 29.96 | 0.916 | 0.95 | ✓ Certified | Wiedemann et al., Nat. Methods 2024 |
| 6 | IsoNet + gradient | 0.722 | 28.32 | 0.887 | 0.92 | ✓ Certified | Liu et al., Nat. Commun. 2021 |
| 7 | IMOD + gradient | 0.625 | 23.5 | 0.75 | 0.95 | ✓ Certified | Kremer et al., J. Struct. Biol. 1996 |
| 8 | SART-ET + gradient | 0.561 | 21.61 | 0.673 | 0.88 | ✓ Certified | Andersen & Kak, Ultrason. Imaging 1984 |
| 9 | WBP + gradient | 0.451 | 17.62 | 0.481 | 0.91 | ✓ Certified | Crowther et al., Proc. R. Soc. 1970 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
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%