fidoptANTs DenoiseImage
ANTs' DenoiseImage, Manjón et al.'s adaptive non-local means for MR, at the command's defaults (Gaussian noise model, patch radius 1, search radius 2): no learnt weights.
SynthesisCPUversion ANTs 2.6.5, release ants-2.6.5-ubuntu-24.04-X64-gcc.zip (sha256 9f6a2c88)MR, MRApache-2.0
Run it
With its KonfAI app, at the benchmark's settings (the fidopt app repositories are private for now: a Hugging Face token with access opens them):
pip install konfai-apps konfai-apps infer fideus-labs/fidopt-synthesis:ANTs_Denoise -i image.nii.gz -o out
The app on Hugging Face: its model, its settings and how it is scored.
Where it works
Its place on each kind of problem it has results on, among the methods ranked there. A method that leads one problem can trail another: read the one closest to yours.
| Problem | Place | Ranked | Datasets |
|---|---|---|---|
| MR to MR, one acquisition to the mean of its repetitions, synthesis | 1 | of 3 | 1 of 1 |
Results
| Dataset | # | Read by | Score | Failed | Time s |
|---|---|---|---|---|---|
| M4Raw, one 0.3 T T2 repetition to the mean of the others | 1 | MAE | 2.5 | 0 | 10 |
- Reference
- Manjón et al., JMRI 2010; Tustison et al., Sci. Rep. 2021