Dataset

DZNE-2026-00479

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Dataset: YODA / Regression is all you need for medical image translation, v1

Rassmann, S.DZNE* ; Kügler, D.DZNE* ; Ewert, C.DZNE* ; Reuter, M.DZNE*

2026
Zenodo

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Please use a persistent id in citations: doi:10.5281/zenodo.19088324  doi:10.5281/ZENODO.19088324

Abstract: 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 (T1w) rs_T1_from_T2w.zip FLAIR -> T2w 1 mm RS (n=2500) Regression YODA, 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.

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Contributing Institute(s):

1. Artificial Intelligence in Medicine (AG Reuter)

Research Program(s):

1. 354 - Disease Prevention and Healthy Aging (POF4-354) (POF4-354)

Appears in the scientific report 2026

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