Dev

Cryo-Electron Tomography (Cryo-ET) — 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_axis_offset -0.72 – 1.08 px
tilt_angle_accuracy -0.24 – 0.36 degpertilt
dose_induced_shrinkage -2.4 – 3.6 -
ctf_per_tilt_variation -0.15 – 0.15 um
missing_wedge 25.2 – 37.2 deg

Dev Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 ETFormer + gradient 0.703 28.61 0.893 0.8 ✓ Certified Chen et al., CVPR 2024
2 DiffusionET + gradient 0.698 28.41 0.889 0.79 ✓ Certified Zhang et al., arXiv 2024
3 DeePiCt + gradient 0.676 26.27 0.839 0.89 ✓ Certified Moebel et al., Nat. Methods 2021
4 DeepDeWedge + gradient 0.636 24.6 0.789 0.87 ✓ Certified Wiedemann et al., Nat. Methods 2024
5 CryoSeg + gradient 0.608 23.22 0.74 0.9 ✓ Certified Lamm et al., Nat. Methods 2022
6 IMOD + gradient 0.584 23.04 0.733 0.8 ✓ Certified Kremer et al., J. Struct. Biol. 1996
7 SART-ET + gradient 0.573 22.33 0.704 0.84 ✓ Certified Andersen & Kak, Ultrason. Imaging 1984
8 IsoNet + gradient 0.538 21.28 0.658 0.81 ✓ Certified Liu et al., Nat. Commun. 2021
9 WBP + gradient 0.475 19.03 0.551 0.82 ✓ Certified Crowther et al., Proc. R. Soc. 1970

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%
Back to Cryo-Electron Tomography (Cryo-ET)