Hidden

Lattice Light-Sheet Microscopy — 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
lattice_period_error -0.7 – 2.3 relative
dithering_range -0.15 – 0.15 -
sheet_na_error -0.007 – 0.023 -
excitation_psf_sidelobe -1.4 – 4.6 relative

Hidden Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 DeconvFormer + gradient 0.743 30.61 0.926 0.83 ✓ Certified Chen et al., CVPR 2024
2 Restormer + gradient 0.704 28.85 0.898 0.78 ✓ Certified Zamir et al., CVPR 2022
3 ScoreMicro + gradient 0.672 27.48 0.869 0.75 ✓ Certified Wei et al., ECCV 2025
4 Wiener Filter + gradient 0.643 25.56 0.819 0.8 ✓ Certified Analytical baseline
5 Restormer+ + gradient 0.642 26.06 0.834 0.74 ✓ Certified Zamir et al., ICCV 2024
6 TV-Deconvolution + gradient 0.640 25.48 0.817 0.79 ✓ Certified Rudin et al., Phys. A 1992
7 DiffDeconv + gradient 0.626 24.27 0.778 0.86 ✓ Certified Huang et al., NeurIPS 2024
8 PnP-FISTA + gradient 0.623 24.05 0.77 0.87 ✓ Certified Bai et al., 2020
9 U-Net + gradient 0.604 23.64 0.755 0.83 ✓ Certified Ronneberger et al., MICCAI 2015
10 ResUNet + gradient 0.598 23.27 0.742 0.84 ✓ Certified DeCelle et al., Nat. Methods 2021
11 Richardson-Lucy + gradient 0.594 23.6 0.754 0.78 ✓ Certified Richardson, JOSA 1972 / Lucy, AJ 1974
12 PnP-DnCNN + gradient 0.593 22.95 0.729 0.86 ✓ Certified Zhang et al., IEEE TIP 2017
13 CARE + gradient 0.547 21.39 0.663 0.84 ✓ Certified Weigert et al., Nat. Methods 2018

Dataset

Scenes: 5

Scoring Formula

0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)

PSNR: 40% SSIM: 40% Consistency: 20%
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