Open dataset · ADC, T2

Medical Decathlon - PROSTATE

Prostate transitional zone and peripheral zone segmentation

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 64 cases into your workspace, run AI models, and segment.

ADC, T2 64 cases CC-BY-SA-4.0 Reference masks
Medical Decathlon - PROSTATE - 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.

prostate_00-t2 - Medical Decathlon - PROSTATE case preview

prostate_00-t2Open

 prostate_01-t2 - Medical Decathlon - PROSTATE case preview

prostate_01-t2Open

 prostate_02-t2 - Medical Decathlon - PROSTATE case preview

prostate_02-t2Open

 prostate_04-t2 - Medical Decathlon - PROSTATE case preview

prostate_04-t2Open

 prostate_06-t2 - Medical Decathlon - PROSTATE case preview

prostate_06-t2Open

 prostate_07-t2 - Medical Decathlon - PROSTATE case preview

prostate_07-t2Open

Open the full dataset in MedSeg → All 64 cases - copy into your workspace to run AI and segment.

About this dataset

Prostate transitional zone and peripheral zone segmentation

FactValue
Cases64
Series64
Size0.2 GB
ModalityADC, T2
Reference masksYes
LicenseCC-BY-SA-4.0
PublisherMedical Decathlon Consortium
Version2022
DOI10.1038/s41467-022-30695-9

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.

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022). The Medical Segmentation Decathlon. Nature Communications, 13(1), 4128.

License: CC-BY-SA-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.

More public datasets