Dev

Ultrasound — 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
sos 1516.0 – 1576.0 m/s
attenuation 0.38 – 0.68 dB/cm/MHz
element_sensitivity -6.0 – 9.0 %
phase_aberration -0.36 – 0.54 rad

Dev Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 BeamDATA + gradient 0.733 29.91 0.915 0.84 ✓ Certified Smith et al., ICCV 2024
2 AttentionBeam + gradient 0.732 30.06 0.918 0.82 ✓ Certified Xu et al., ECCV 2024
3 UltrasoundFormer + gradient 0.721 29.76 0.913 0.79 ✓ Certified Park et al., CVPR 2024
4 BeamFormer + gradient 0.711 28.06 0.882 0.89 ✓ Certified Li et al., ICCV 2024
5 Phase-ADMM-Net + gradient 0.670 26.77 0.852 0.81 ✓ Certified Hou et al., IEEE TMI 2022
6 ScoreUS + gradient 0.662 25.68 0.823 0.88 ✓ Certified Johnson et al., ECCV 2025
7 DiffUS + gradient 0.634 25.12 0.806 0.8 ✓ Certified Chen et al., NeurIPS 2024
8 PW-DAS + gradient 0.608 23.88 0.764 0.82 ✓ Certified Plane wave synthesis baseline
9 ABLE + gradient 0.600 23.44 0.748 0.83 ✓ Certified Luijten et al., IEEE TMI 2020
10 MU-Net + gradient 0.582 23.16 0.737 0.78 ✓ Certified Hyun et al., IEEE TUFFC 2022
11 PnP-ADMM + gradient 0.580 22.37 0.706 0.87 ✓ Certified Goudarzi et al., 2020
12 DAS + gradient 0.562 21.84 0.683 0.85 ✓ Certified Analytical baseline
13 DAS-CF + gradient 0.560 22.31 0.703 0.78 ✓ Certified Capon filter, IEEE 1969
14 PnP-TV + gradient 0.492 19.27 0.563 0.87 ✓ Certified TV regularization for ultrasound

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%
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