Open dataset · MR

TotalSegmentator — Liver Couinaud Segments (MR)

Manual segmentation of the 9 Couinaud liver segments — anatomical reference for surgery planning.

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MR 59 cases CC-BY-4.0 Reference masks Pathology
TotalSegmentator — Liver Couinaud Segments (MR) — example case rendered in the MedSeg editor
Example case with its reference segmentation — straight from the catalog, rendered by MedSeg.

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kbdGS2laG0N4H0q6 — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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 YIMSjo3ZL9jfEIsC — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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 1TXdtAw1x4e9dHvl — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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 1oqsYgz8VneMqTBF — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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 3kz5yIBfcwwl7sLm — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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 4fBAadbkrWlohMl5 — TotalSegmentator — Liver Couinaud Segments (MR) case preview

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About this dataset

TotalSegmentator Liver Couinaud Segments — MR. Abdominal MR scans with manual segmentation of the 9 Couinaud liver segments, the standard surgical/radiological anatomical reference for liver intervention planning. Wasserthal et al. 2026 (Zenodo 20272492). nnU-Net v2 format.

Note on case count: Wasserthal's release ships 120 cases, but ~50% had empty labels (brain-MR-like 0.34 mm voxels with no liver visible — likely a curation mistake). MedSeg filters those out on import, so the catalog shows only cases that actually contain liver-segment annotations.

FactValue
Cases59
Series59
Size0.6 GB
ModalityMR
Reference masksYes
LicenseCC-BY-4.0
PublisherUniversity Hospital Basel
Version2026-05
DOI10.5281/zenodo.20272492

What you can do with it in MedSeg

Copied cases behave like normal project series — the public image bytes are linked, not duplicated, so copies are instant and take no extra storage.

  1. Copy cases into a project.
    Filter, multi-select, copy — reference masks come along if you want them.
  2. Run AI segmentation.
    TotalSegmentator, MRSegmentator, nnInteractive 3D clicks/scribbles, or text-prompted VoxTell.
  3. Edit and measure.
    Brush, lasso, fill, oblique planes, volumes in ml — in the browser.
  4. Train your own nnU-Net.
    Correct masks on a handful of cases and train a custom model on hosted GPUs.

Citation

If you use this dataset in your research, cite the source per its license terms.

Wasserthal, J., et al. (2026). TotalSegmentator subtask training datasets. Zenodo.

License: CC-BY-4.0

Open data still carries obligations — attribution at minimum. Check the license terms and the source publication before publishing work built on this dataset. MedSeg is a research tool, not a medical device.

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