Public

Secondary Ion Mass Spectrometry (SIMS) Imaging — Public Tier

(5 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
mass_calibration_drift -1.0 – 2.0 0.5 ppm
matrix_effect_(sputter_yield) -10.0 – 20.0 5.0 -
crater_edge_effect -2.0 – 4.0 1.0 -
charging_(insulating_samples) -40.0 – 80.0 20.0 V

InverseNet Baseline Scores

Method: CPU_baseline — Mismatch parameter: nominal

Scenario I (Ideal)

20.86 dB

SSIM 0.5556

Scenario II (Mismatch)

17.94 dB

SSIM 0.2739

Scenario III (Oracle)

21.09 dB

SSIM 0.4477

Per-scene breakdown (4 scenes)
Scene PSNR I SSIM I PSNR II SSIM II PSNR III SSIM III
scene_00 22.20 0.5293 20.35 0.2280 21.93 0.3469
scene_01 22.95 0.6386 19.17 0.3063 21.54 0.4791
scene_02 17.62 0.5116 14.75 0.2820 20.16 0.5023
scene_03 20.65 0.5429 17.50 0.2793 20.72 0.4626

Public Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 ScoreSpectra + gradient 0.772 31.37 0.935 0.92 ✓ Certified Wei et al., 2025
2 U-Net-Spectra + gradient 0.760 31.21 0.934 0.87 ✓ Certified Spectral U-Net variant
3 CDAE + gradient 0.756 30.33 0.922 0.92 ✓ Certified Zhang et al., Sensors 2024
4 Cascade-UNet + gradient 0.752 30.2 0.92 0.91 ✓ Certified Physics-informed UNet, 2025
5 PINN-Spectra + gradient 0.734 29.46 0.908 0.88 ✓ Certified Physics-informed neural network
6 SpectraFormer + gradient 0.720 28.78 0.896 0.87 ✓ Certified Spectroscopy transformer, 2024
7 DiffusionSpectra + gradient 0.716 28.31 0.887 0.89 ✓ Certified Zhang et al., 2024
8 PnP-DnCNN + gradient 0.695 26.88 0.855 0.92 ✓ Certified Zhang et al., 2017
9 Baseline Correction + gradient 0.587 22.42 0.708 0.9 ✓ Certified Polynomial fitting baseline
10 SG-ALS + gradient 0.577 22.17 0.697 0.88 ✓ Certified Savitzky-Golay + ALS baseline
11 SVD + gradient 0.565 21.73 0.678 0.88 ✓ Certified Singular Value Decomposition

Visible Data Fields

y H_ideal spec_ranges x_true true_spec

Dataset

Format: HDF5
Scenes: 5

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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