fidoptDIPY non-local means
DIPY's blockwise non-local means with a Rician noise model, the noise's level estimated from the image by estimate_sigma, both at their defaults: no learnt weights.
SynthesisCPUversion dipy 1.12.1MR, MRBSD-3-Clause
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:DIPY_NLMeans -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 | 2 | 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 | 2 | MAE | 2.8 | 0 | 8 |
- Reference
- Garyfallidis et al., Front. Neuroinform. 2014; Coupé et al., IEEE TMI 2008