Public

Three-Photon Microscopy — Public Tier

(5 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
scattering_coeff 10.0 – 25.0 17.5 mm^-1
excitation_wavelength_shift -2.0 – 4.0 1.0 nm
depth_dependent_psf -0.4 – 0.8 0.2 -

InverseNet Baseline Scores

Method: CPU_baseline — Mismatch parameter: nominal

Scenario I (Ideal)

13.27 dB

SSIM 0.3991

Scenario II (Mismatch)

11.88 dB

SSIM 0.2385

Scenario III (Oracle)

19.75 dB

SSIM 0.4579

Per-scene breakdown (4 scenes)
Scene PSNR I SSIM I PSNR II SSIM II PSNR III SSIM III
scene_00 17.02 0.3838 14.94 0.2440 20.04 0.5013
scene_01 14.23 0.2969 12.92 0.2098 19.23 0.5480
scene_02 8.52 0.3871 8.01 0.2308 20.11 0.3417
scene_03 13.30 0.5284 11.66 0.2694 19.61 0.4408

Public Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 ScoreMicro + gradient 0.827 35.78 0.972 0.9 ✓ Certified Wei et al., ECCV 2025
2 DiffDeconv + gradient 0.822 35.41 0.97 0.9 ✓ Certified Huang et al., NeurIPS 2024
3 Restormer+ + gradient 0.816 35.12 0.968 0.89 ✓ Certified Zamir et al., ICCV 2024
4 DeconvFormer + gradient 0.811 34.39 0.964 0.91 ✓ Certified Chen et al., CVPR 2024
5 U-Net + gradient 0.808 33.83 0.96 0.93 ✓ Certified Ronneberger et al., MICCAI 2015
6 Restormer + gradient 0.793 33.18 0.954 0.9 ✓ Certified Zamir et al., CVPR 2022
7 ResUNet + gradient 0.792 32.95 0.952 0.91 ✓ Certified DeCelle et al., Nat. Methods 2021
8 CARE + gradient 0.772 31.54 0.937 0.91 ✓ Certified Weigert et al., Nat. Methods 2018
9 PnP-DnCNN + gradient 0.750 29.83 0.914 0.93 ✓ Certified Zhang et al., IEEE TIP 2017
10 TV-Deconvolution + gradient 0.723 28.35 0.888 0.92 ✓ Certified Rudin et al., Phys. A 1992
11 PnP-FISTA + gradient 0.704 27.48 0.869 0.91 ✓ Certified Bai et al., 2020
12 Wiener Filter + gradient 0.664 25.48 0.817 0.91 ✓ Certified Analytical baseline
13 Richardson-Lucy + gradient 0.648 25.13 0.806 0.87 ✓ Certified Richardson, JOSA 1972 / Lucy, AJ 1974

Visible Data Fields

y H_ideal spec_ranges x_true true_spec

Dataset

Format: HDF5
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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