Dev
SPECT — 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 |
|---|---|---|
| center_offset | -1.8 – 2.7 | pixels |
| collimator_septal | -0.024 – 0.036 | |
| attenuation | -6.0 – 9.0 | % |
| scatter | 0.14 – 0.29 |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PET-ViT + gradient | 0.781 | 33.6 | 0.958 | 0.81 | ✓ Certified | Smith et al., ICCV 2024 |
| 2 | PETFormer + gradient | 0.764 | 31.25 | 0.934 | 0.89 | ✓ Certified | Li et al., ECCV 2024 |
| 3 | FBP-PET + gradient | 0.693 | 27.21 | 0.863 | 0.88 | ✓ Certified | Analytical baseline |
| 4 | TransEM + gradient | 0.691 | 27.83 | 0.877 | 0.81 | ✓ Certified | Xie et al., 2023 |
| 5 | ML-EM + gradient | 0.683 | 27.06 | 0.86 | 0.84 | ✓ Certified | Shepp & Vardi, IEEE TPAMI 1982 |
| 6 | DeepPET + gradient | 0.653 | 25.36 | 0.813 | 0.87 | ✓ Certified | Haggstrom et al., MIA 2019 |
| 7 | MAPEM-RDP + gradient | 0.643 | 25.08 | 0.805 | 0.85 | ✓ Certified | Nuyts et al., IEEE TMI 2002 |
| 8 | U-Net-PET + gradient | 0.630 | 25.11 | 0.806 | 0.78 | ✓ Certified | Ronneberger et al. variant, MICCAI 2020 |
| 9 | OS-EM + gradient | 0.621 | 23.91 | 0.765 | 0.88 | ✓ Certified | Hudson & Larkin, IEEE TMI 1994 |
| 10 | OSEM + gradient | 0.553 | 21.81 | 0.682 | 0.81 | ✓ 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%