Dev
CT + Fluorescence (FLIT) — Dev Tier
(3 scenes)Blind evaluation tier — no ground truth available.
What you get
Measurements (y), ideal forward operator (H), and spec ranges only.
How to use
Apply your pipeline from the Public tier. Use consistency as self-check.
What to submit
Reconstructed signals and corrected spec. Scored server-side.
Parameter Specifications
🔒
True spec hidden — estimate parameters from spec ranges below.
| Parameter | Spec Range | Unit |
|---|---|---|
| optical_property_assignment_error | -7.2 – 10.8 | - |
| autofluorescence | -12.0 – 18.0 | - |
| registration_(ct_to_optical) | -0.72 – 1.08 | mm |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffusionXRF + gradient | 0.774 | 32.32 | 0.946 | 0.86 | ✓ Certified | Song et al., ICLR 2021 (XRF adapt.) |
| 2 | PnP-XRF + gradient | 0.760 | 30.99 | 0.931 | 0.89 | ✓ Certified | Chan et al., IEEE TIP 2016 (XRF adapt.) |
| 3 | SwinXRF + gradient | 0.748 | 31.48 | 0.937 | 0.79 | ✓ Certified | Liu et al., ICCV 2021 (XRF adapt.) |
| 4 | PhysXRF-Net + gradient | 0.711 | 28.48 | 0.891 | 0.85 | ✓ Certified | Raissi et al., J. Comput. Phys. 2019 (XRF) |
| 5 | U-Net-XRF + gradient | 0.651 | 25.08 | 0.805 | 0.89 | ✓ Certified | Ronneberger et al., MICCAI 2015 (XRF adapt.) |
| 6 | DnCNN-XRF + gradient | 0.606 | 23.16 | 0.737 | 0.9 | ✓ Certified | Zhang et al., IEEE TIP 2017 (XRF adapt.) |
| 7 | MLEM-XRF + gradient | 0.600 | 23.61 | 0.754 | 0.81 | ✓ Certified | Jaszczak et al., IEEE TNS 1981 (XRF adapt.) |
| 8 | TV-XRFCT + gradient | 0.529 | 20.61 | 0.628 | 0.86 | ✓ Certified | Larsson et al., Phys. Med. Biol. 2020 |
| 9 | FBP-XRF + gradient | 0.478 | 18.87 | 0.543 | 0.86 | ✓ Certified | Boisseau & Grodzins, Hyperfine Int. 1987 |
Visible Data Fields
y
H_ideal
spec_ranges
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%