Dev
SPECT/CT — 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 |
|---|---|---|
| ct_registration_shift | -6.0 – 9.0 | pixels |
| hu_to_mu_scale | -14.4 – 21.6 | % |
| scatter_fraction | -0.42 – 0.63 | |
| collimator_blur | -1.7 – 8.8 | pixels |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DL-SPECT + gradient | 0.724 | 28.75 | 0.896 | 0.89 | ✓ Certified | Ramon et al., IEEE TMI 2020 |
| 2 | MAP-OSEM + gradient | 0.699 | 28.57 | 0.892 | 0.78 | ✓ Certified | Nuyts et al., 2002 |
| 3 | AC-OSEM + gradient | 0.690 | 27.77 | 0.876 | 0.81 | ✓ Certified | CT-based attenuation correction |
| 4 | OSEM + gradient | 0.513 | 20.06 | 0.602 | 0.86 | ✓ Certified | Hudson & Larkin, IEEE TMI 1994 |
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%