Public
Brillouin 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 |
|---|---|---|---|
| brillouin_shift_calibration | -10.0 – 20.0 | 5.0 | MHz |
| vipa_fsr_error | -0.1 – 0.2 | 0.05 | - |
| elastic_scattering_leakage | -12.0 – 6.0 | -3.0 | - |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
20.86 dB
SSIM 0.5556
Scenario II (Mismatch)
17.94 dB
SSIM 0.2739
Scenario III (Oracle)
21.09 dB
SSIM 0.4477
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 22.20 | 0.5293 | 20.35 | 0.2280 | 21.93 | 0.3469 |
| scene_01 | 22.95 | 0.6386 | 19.17 | 0.3063 | 21.54 | 0.4791 |
| scene_02 | 17.62 | 0.5116 | 14.75 | 0.2820 | 20.16 | 0.5023 |
| scene_03 | 20.65 | 0.5429 | 17.50 | 0.2793 | 20.72 | 0.4626 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | SpectraFormer + gradient | 0.848 | 36.69 | 0.977 | 0.95 | ✓ Certified | Chen et al., arXiv 2023 |
| 2 | DiffusionSpectra + gradient | 0.839 | 36.85 | 0.977 | 0.9 | ✓ Certified | Gao et al., Nat. Methods 2024 |
| 3 | PINN-Brillouin + gradient | 0.808 | 34.29 | 0.963 | 0.9 | ✓ Certified | Raissi et al., J. Comput. Phys. 2019 (adapted) |
| 4 | U-Net-Spectral + gradient | 0.799 | 33.93 | 0.96 | 0.88 | ✓ Certified | Ronneberger et al., MICCAI 2015 (spectral) |
| 5 | CDAE + gradient | 0.780 | 32.35 | 0.946 | 0.89 | ✓ Certified | Zhang et al., Sensors 2024 |
| 6 | CNN-Spectra + gradient | 0.758 | 30.46 | 0.924 | 0.92 | ✓ Certified | Remer & Bhatt, Biomed. Opt. Express 2020 |
| 7 | DnCNN-Brillouin + gradient | 0.757 | 30.61 | 0.926 | 0.9 | ✓ Certified | Zhang et al., IEEE TIP 2017 (adapted) |
| 8 | SG-Baseline + gradient | 0.662 | 25.7 | 0.823 | 0.88 | ✓ Certified | Savitzky & Golay, Anal. Chem. 1964 |
| 9 | Lorentzian-Fit + gradient | 0.614 | 23.47 | 0.749 | 0.9 | ✓ Certified | Dil, Rep. Prog. Phys. 1982 |
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%