Public
Photoacoustic — 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 |
|---|---|---|---|
| sos | 1520.0 – 1580.0 | 1550.0 | m/s |
| fluence | -10.0 – 20.0 | 5.0 | % |
| sensor_response | -5.0 – 10.0 | 2.5 | % |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
14.57 dB
SSIM 0.0990
Scenario II (Mismatch)
14.40 dB
SSIM 0.0397
Scenario III (Oracle)
14.08 dB
SSIM 0.0440
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 14.04 | 0.0090 | 13.60 | 0.0071 | 13.09 | 0.0073 |
| scene_01 | 16.19 | 0.0131 | 16.08 | 0.0126 | 15.84 | 0.0100 |
| scene_02 | 12.09 | 0.3322 | 12.36 | 0.1170 | 12.32 | 0.1422 |
| scene_03 | 15.97 | 0.0415 | 15.59 | 0.0223 | 15.09 | 0.0167 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PAT-Former + gradient | 0.764 | 31.37 | 0.935 | 0.88 | ✓ Certified | PAT reconstruction transformer, 2024 |
| 2 | Deep-PAI + gradient | 0.730 | 29.1 | 0.902 | 0.89 | ✓ Certified | Hauptmann et al., IEEE TMI 2018 |
| 3 | PnP-ADMM + gradient | 0.641 | 24.74 | 0.794 | 0.88 | ✓ Certified | Goudarzi et al., 2020 |
| 4 | Universal Back-Proj + gradient | 0.542 | 20.8 | 0.636 | 0.9 | ✓ Certified | Xu & Wang, Phys. Rev. E 2005 |
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%