YODA / Regression is all you need for medical image translation
Model weights and singularity/apptainer environment for YODA (Regression is all you need for medical image translation, 2026, IEEE T-MI) and extensions (ISMRM 2026). Please note the usage instruction at <a href="https://github.com
Model weights and singularity/apptainer environment for YODA (Regression is all you need for medical image translation, 2026, IEEE T-MI) and extensions (ISMRM 2026).
Please note the usage instruction at github.com/Deep-MI/YODA. The provided dagobah.sif file is a pre-build Singularity/Apptainer container, ie the result from singularity build dagobah.sif docker://srassmann/dif:latest.
If you use the resources in your research, please always cite the YODA paper + checkpoint-specific additional (conference) papers.
| Checkpoint | Trans. Task | Resolution | Train. Dataset | Train. Paradigm | Citation(s) |
rs_FLAIR_from_T1T2.zip | T1w+T2w -> FLAIR | 1 mm | RS (n=1344) | Diffusion | YODA |
brats_FLAIR_from_T1T2.zip | T1w+T2w -> FLAIR | 1 mm (resampled) | BraTS ’23 (n=1270) | Diffusion | YODA |
rs_FLAIR_from_T1.zip | T1w -> FLAIR | 1 mm | RS (n=1344) | Diffusion | YODA, ISMRM 2026 (FLAIR) |
rs_FLAIR_from_T2.zip | T2w -> FLAIR | 1 mm | RS (n=1344) | Diffusion | YODA, ISMRM 2026 (FLAIR) |
ixi_T2_from_T1PD.zip | T1w+PD -> T2w | ~1 mm | IXI (n=511) | Diffusion | YODA |
GoldAtlas_CT_from_MR.zip | T1w+T2w -> CT | ~1x1x3 mm | Gold Atlas (n=11) | Diffusion | YODA |
rs_T1_from_FLAIR.zip | FLAIR -> T1w | 1 mm | RS (n=2500) | Regression | YODA, ISMRM 2026 (T2_FS) |
rs_T1_from_T2w.zip | FLAIR -> T2w | 1 mm | RS (n=2500) | Regression | YODA, ISMRM 2026 (T2_FS) |
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