Dev
Neutron Tomo — 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 |
|---|---|---|
| beam_spectrum | -3.6 – 5.4 | % |
| scatter_correction | -6.0 – 9.0 | % |
| rotation_offset | -1.2 – 1.8 | pixels |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PETFormer + gradient | 0.724 | 28.79 | 0.896 | 0.89 | ✓ Certified | Li et al., ECCV 2024 |
| 2 | TransEM + gradient | 0.642 | 24.97 | 0.801 | 0.86 | ✓ Certified | Xie et al., 2023 |
| 3 | FBP-PET + gradient | 0.636 | 25.07 | 0.804 | 0.82 | ✓ Certified | Analytical baseline |
| 4 | DeepPET + gradient | 0.618 | 24.36 | 0.781 | 0.81 | ✓ Certified | Haggstrom et al., MIA 2019 |
| 5 | PET-ViT + gradient | 0.605 | 23.99 | 0.768 | 0.79 | ✓ Certified | Smith et al., ICCV 2024 |
| 6 | U-Net-PET + gradient | 0.600 | 23.37 | 0.745 | 0.84 | ✓ Certified | Ronneberger et al. variant, MICCAI 2020 |
| 7 | MAPEM-RDP + gradient | 0.562 | 21.94 | 0.687 | 0.84 | ✓ Certified | Nuyts et al., IEEE TMI 2002 |
| 8 | ML-EM + gradient | 0.557 | 21.59 | 0.672 | 0.86 | ✓ Certified | Shepp & Vardi, IEEE TPAMI 1982 |
| 9 | OS-EM + gradient | 0.515 | 20.46 | 0.621 | 0.81 | ✓ Certified | Hudson & Larkin, IEEE TMI 1994 |
| 10 | OSEM + gradient | 0.504 | 19.75 | 0.587 | 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%