Hidden
CT + Fluorescence (FLIT) — 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 |
|---|---|---|
| optical_property_assignment_error | -4.2 – 13.8 | - |
| autofluorescence | -7.0 – 23.0 | - |
| registration_(ct_to_optical) | -0.42 – 1.38 | mm |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffusionXRF + gradient | 0.745 | 31.46 | 0.937 | 0.78 | ✓ Certified | Song et al., ICLR 2021 (XRF adapt.) |
| 2 | PnP-XRF + gradient | 0.736 | 29.72 | 0.912 | 0.87 | ✓ Certified | Chan et al., IEEE TIP 2016 (XRF adapt.) |
| 3 | SwinXRF + gradient | 0.692 | 28.32 | 0.887 | 0.77 | ✓ Certified | Liu et al., ICCV 2021 (XRF adapt.) |
| 4 | PhysXRF-Net + gradient | 0.653 | 25.99 | 0.832 | 0.8 | ✓ Certified | Raissi et al., J. Comput. Phys. 2019 (XRF) |
| 5 | U-Net-XRF + gradient | 0.587 | 22.73 | 0.72 | 0.86 | ✓ Certified | Ronneberger et al., MICCAI 2015 (XRF adapt.) |
| 6 | MLEM-XRF + gradient | 0.563 | 22.54 | 0.713 | 0.76 | ✓ Certified | Jaszczak et al., IEEE TNS 1981 (XRF adapt.) |
| 7 | DnCNN-XRF + gradient | 0.494 | 19.56 | 0.577 | 0.84 | ✓ Certified | Zhang et al., IEEE TIP 2017 (XRF adapt.) |
| 8 | FBP-XRF + gradient | 0.458 | 18.19 | 0.509 | 0.86 | ✓ Certified | Boisseau & Grodzins, Hyperfine Int. 1987 |
| 9 | TV-XRFCT + gradient | 0.453 | 18.84 | 0.542 | 0.74 | ✓ Certified | Larsson et al., Phys. Med. Biol. 2020 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%