Public

Neutron Tomo — Public Tier

(3 scenes)

Full-access development tier with all data visible.

What you get

Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.

How to use

Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.

What to submit

Reconstructed signals (x_hat) and corrected spec as HDF5.

Parameter Specifications

True spec visible — use these exact values for Scenario III oracle reconstruction.

Parameter Spec Range True Value Unit
beam_spectrum -3.0 – 6.0 1.5 %
scatter_correction -5.0 – 10.0 2.5 %
rotation_offset -1.0 – 2.0 0.5 pixels

InverseNet Baseline Scores

Method: CPU_baseline — Mismatch parameter: nominal

Scenario I (Ideal)

17.61 dB

SSIM 0.3262

Scenario II (Mismatch)

13.04 dB

SSIM 0.0468

Scenario III (Oracle)

16.34 dB

SSIM 0.1224

Per-scene breakdown (4 scenes)
Scene PSNR I SSIM I PSNR II SSIM II PSNR III SSIM III
scene_00 16.58 0.3251 12.51 0.0447 15.93 0.1214
scene_01 18.88 0.3252 13.74 0.0480 17.02 0.1162
scene_02 18.30 0.3298 13.37 0.0496 16.55 0.1259
scene_03 16.68 0.3248 12.53 0.0450 15.85 0.1262

Public Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 PETFormer + gradient 0.804 33.69 0.958 0.92 ✓ Certified Li et al., ECCV 2024
2 DeepPET + gradient 0.769 31.02 0.931 0.93 ✓ Certified Haggstrom et al., MIA 2019
3 TransEM + gradient 0.764 31.28 0.934 0.89 ✓ Certified Xie et al., 2023
4 U-Net-PET + gradient 0.719 28.7 0.895 0.87 ✓ Certified Ronneberger et al. variant, MICCAI 2020
5 PET-ViT + gradient 0.717 28.47 0.89 0.88 ✓ Certified Smith et al., ICCV 2024
6 MAPEM-RDP + gradient 0.679 26.58 0.848 0.87 ✓ Certified Nuyts et al., IEEE TMI 2002
7 FBP-PET + gradient 0.673 25.84 0.827 0.92 ✓ Certified Analytical baseline
8 OS-EM + gradient 0.603 22.71 0.72 0.94 ✓ Certified Hudson & Larkin, IEEE TMI 1994
9 ML-EM + gradient 0.602 22.99 0.731 0.9 ✓ Certified Shepp & Vardi, IEEE TPAMI 1982
10 OSEM + gradient 0.594 22.99 0.731 0.86 ✓ Certified Hudson & Larkin, IEEE TMI 1994

Visible Data Fields

y H_ideal spec_ranges x_true true_spec

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%
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