Hidden
Electrical Impedance Tomography (EIT) — 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 |
|---|---|---|
| contact_impedance | 86.0 – 146.0 | ohm |
| electrode_position_error | -0.28 – 0.92 | mm |
| background_conductivity | 0.172 – 0.292 | S/m |
| current_amplitude_drift | 0.993 – 1.023 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | EIT-Former + gradient | 0.512 | 20.27 | 0.612 | 0.82 | ✓ Certified | EIT reconstruction transformer, 2024 |
| 2 | D-bar CNN + gradient | 0.404 | 16.8 | 0.44 | 0.8 | ✓ Certified | Hamilton & Hauptmann, IEEE TMI 2018 |
| 3 | TV-ADMM + gradient | 0.386 | 16.18 | 0.41 | 0.8 | ✓ Certified | Borsic et al., Physiol. Meas. 2010 |
| 4 | Gauss-Newton + gradient | 0.378 | 15.51 | 0.378 | 0.86 | ✓ Certified | Cheney et al., SIAM Rev. 1999 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%