Open dataset · CT

TotalSegmentator — Hip Implant

71 CT cases with manual hip-implant segmentations. Post-arthroplasty patients.

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CT 71 cases CC-BY-4.0 Reference masks Pathology
TotalSegmentator — Hip Implant — example case rendered in the MedSeg editor
Example case with its reference segmentation — straight from the catalog, rendered by MedSeg.

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sGsD88XTqiIRGFLe — TotalSegmentator — Hip Implant case preview

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 EfVSd2gHagvkCyD0 — TotalSegmentator — Hip Implant case preview

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 3gmXcSq12lqKtAkS — TotalSegmentator — Hip Implant case preview

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 51DNcJ4zvuQeaIEd — TotalSegmentator — Hip Implant case preview

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 67dYZaq6hSbQszWc — TotalSegmentator — Hip Implant case preview

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 6LcXiHv2QR52uIOe — TotalSegmentator — Hip Implant case preview

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About this dataset

TotalSegmentator Hip Implant — 71 CT cases with manual segmentations of hip prostheses (acetabular cup + femoral stem + head). Post-total-hip-arthroplasty patients. Wasserthal et al. 2026. Useful for orthopedic post-op imaging and implant-related artifact handling. nnU-Net v2 format.

FactValue
Cases71
Series71
Size9.1 GB
ModalityCT
Reference masksYes
LicenseCC-BY-4.0
PublisherUniversity Hospital Basel
Version2026-05
DOI10.5281/zenodo.20272031

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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