Hidden
Digital Breast Tomosynthesis (DBT) — Hidden Tier
(3 scenes)Fully blind server-side evaluation — no data download.
What you get
No data downloadable. Algorithm runs server-side on hidden measurements.
How to use
Package algorithm as Docker container / Python script. Submit via link.
What to submit
Containerized algorithm accepting y + H, outputting x_hat + corrected spec.
Parameter Specifications
🔒
True spec hidden — blind evaluation, only ranges available.
| Parameter | Spec Range | Unit |
|---|---|---|
| angular_range_error | -0.28 – 0.92 | degtotal |
| detector_motion_blur | -0.07 – 0.23 | px |
| scatter_fraction | 0.258 – 0.438 | - |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PhysDBT + gradient | 0.719 | 29.52 | 0.909 | 0.8 | ✓ Certified | Nett et al., IEEE TMI 2024 |
| 2 | SwinDBT + gradient | 0.672 | 26.26 | 0.839 | 0.87 | ✓ Certified | Li et al., Med. Phys. 2023 |
| 3 | DiffusionDBT + gradient | 0.664 | 25.95 | 0.831 | 0.86 | ✓ Certified | Gao et al., MICCAI 2024 |
| 4 | TransDBT + gradient | 0.608 | 23.69 | 0.757 | 0.84 | ✓ Certified | Wang et al., MICCAI 2022 |
| 5 | DuDoRNet-DBT + gradient | 0.594 | 23.44 | 0.748 | 0.8 | ✓ Certified | Zhou et al., CVPR 2020 |
| 6 | SART-DBT + gradient | 0.573 | 22.66 | 0.717 | 0.8 | ✓ Certified | Andersen & Kak, Ultrason. Imaging 1984 |
| 7 | DnCNN-DBT + gradient | 0.559 | 22.47 | 0.71 | 0.75 | ✓ Certified | Chen et al., IEEE TMI 2018 |
| 8 | FBP-DBT + gradient | 0.502 | 20.29 | 0.613 | 0.77 | ✓ Certified | Sechopoulos, Med. Phys. 2013 |
| 9 | TV-DBT + gradient | 0.326 | 13.62 | 0.294 | 0.86 | ✓ Certified | Sidky et al., Med. Phys. 2014 |
Dataset
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%