Hidden
Functional Near-Infrared Spectroscopy (fNIRS) — Hidden Tier
(3 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 |
|---|---|---|
| source_detector_coupling | 0.93 – 1.23 | - |
| scalp_brain_distance_variation | -0.7 – 2.3 | mm |
| motion_artifact_(head) | -1.4 – 4.6 | - |
| systemic_physiology_contamination | -4.2 – 13.8 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | MBLL + gradient | 0.666 | 26.13 | 0.836 | 0.85 | ✓ Certified | Cope & Delpy, Med. Biol. Eng. Comput. 1988 |
| 2 | DL-DOT + gradient | 0.652 | 25.52 | 0.818 | 0.85 | ✓ Certified | Yoo et al., IEEE TMI 2020 |
| 3 | PnP-DOT + gradient | 0.635 | 24.74 | 0.794 | 0.85 | ✓ Certified | Yoo et al., IEEE TMI 2020 |
| 4 | Tikhonov-DOT + gradient | 0.558 | 22.45 | 0.709 | 0.75 | ✓ Certified | Arridge, Inverse Probl. 1999 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%