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YODA / Regression is all you need for medical image translation

Domain:

healthcare

Record type:

modelsoftware
Creator:
RasKügEweReu
Publisher:
Zenodo
Host:avatar

Model weights and singularity/apptainer environment for YODA (Regression is all you… 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.

CheckpointTrans. TaskResolutionTrain. Dataset Train. ParadigmCitation(s)
rs_FLAIR_from_T1T2.zipT1w+T2w -> FLAIR1 mmRS (n=1344)DiffusionYODA
brats_FLAIR_from_T1T2.zipT1w+T2w -> FLAIR1 mm (resampled)BraTS '23 (n=1270)DiffusionYODA
rs_FLAIR_from_T1.zipT1w -> FLAIR1 mmRS (n=1344)DiffusionYODA, ISMRM 2026 (FLAIR)
rs_FLAIR_from_T2.zipT2w -> FLAIR1 mmRS (n=1344)DiffusionYODA, ISMRM 2026 (FLAIR) 
ixi_T2_from_T1PD.zipT1w+PD -> T2w~1 mmIXI (n=511)DiffusionYODA
GoldAtlas_CT_from_MR.zipT1w+T2w -> CT~1x1x3 mmGold Atlas (n=11)DiffusionYODA
rs_T1_from_FLAIR.zipFLAIR -> T1w1 mmRS (n=2500)RegressionYODA, ISMRM 2026 (T1w)
rs_T1_from_T2w.zipFLAIR -> T2w1 mmRS (n=2500)RegressionYODA, ISMRM 2026 (T1w)
 
Citations:
YODA: Rassmann et al. (2026) "Regression is all you need for medical image translation", IEEE Transactions on Medical Imaging
ISMRM 2026 (FLAIR): Rassmann et al. (2026) "FLAIR-less white-matter hyperintensity segmentation using YODA", ISMRM 2026 (Cape Town)
ISMRM 2026 (T1w): Rassmann et al. (2026) "MRI contrast translation for full-brain segmentation from T2-weighted contrasts", ISMRM 2026 (Cape Town)
 
Note: Depending on the Training Paradigm, the checkpoints require either the diffusion (dm_predict.py) or regression (reg_predict.py) inference scripts.
 
The file expected_output-FLAIR_from_T1T2.nii.gz is obtained from running the respective T1w+T2w->FLAIR translator on the example RS case.

Visit

doi.org

Tasks

computer vision

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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