Open dataset · CT

TotalSegmentator - Liver Lesions (CT)

842 CT cases with manual liver-lesion segmentations. Real clinical oncology cohort.

Open a sample case in your browser Open the full dataset in MedSeg →

The sample cases below open read-only in the MedSeg editor - no account needed. Open the full dataset to copy all 842 cases into your workspace, run AI models, and segment.

CT 842 cases CC-BY-4.0 Reference masks Pathology
TotalSegmentator - Liver Lesions (CT) - example case rendered in the MedSeg editor
Example case with its reference segmentation - straight from the catalog, rendered by MedSeg.

Browse sample cases

These cases open instantly in the browser-based editor - scroll the slices, inspect the reference masks, window the image. No account needed.

038lIVt2WjmwWJc6 - TotalSegmentator - Liver Lesions (CT) case preview

038lIVt2WjmwWJc6Open

 0AbJHdnCKYU14XnY - TotalSegmentator - Liver Lesions (CT) case preview

0AbJHdnCKYU14XnYOpen

 0LHth9cfqxoisxhI - TotalSegmentator - Liver Lesions (CT) case preview

0LHth9cfqxoisxhIOpen

 0R65xRVtCrSfrJQC - TotalSegmentator - Liver Lesions (CT) case preview

0R65xRVtCrSfrJQCOpen

 86FNMi2QiFmquhyj - TotalSegmentator - Liver Lesions (CT) case preview

86FNMi2QiFmquhyjOpen

 LIXccrDJ5ADyoANq - TotalSegmentator - Liver Lesions (CT) case preview

LIXccrDJ5ADyoANqOpen

Open the full dataset in MedSeg → All 842 cases - copy into your workspace to run AI and segment.

About this dataset

TotalSegmentator Liver Lesions - 842 CT cases with manual liver lesion segmentations (HCC, metastases, and other focal liver lesions). Wasserthal et al. 2026 training dataset for the TS liver-lesion subtask model. Real clinical oncology data from University Hospital Basel and partner sites. nnU-Net v2 format.

FactValue
Cases842
Series842
Size39.0 GB
ModalityCT
Reference masksYes
LicenseCC-BY-4.0
PublisherUniversity Hospital Basel
Version2026-05
DOI10.5281/zenodo.20272572

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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