Open dataset · CT

LIDC-IDRI - Lung CT with nodule pathology

1010 lung CT scans from 4 institutions, with marked-up nodules from 4 radiologists. Real clinical, multi-vendor.

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 1,010 cases into your workspace, run AI models, and segment.

CT 1,010 cases CC-BY-3.0 Reference masks Pathology
LIDC-IDRI - Lung CT with nodule pathology - 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.

LIDC-IDRI-0001 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0001Open

 LIDC-IDRI-0002 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0002Open

 LIDC-IDRI-0003 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0003Open

 LIDC-IDRI-0004 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0004Open

 LIDC-IDRI-0426 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0426Open

 LIDC-IDRI-0888 - LIDC-IDRI - Lung CT with nodule pathology case preview

LIDC-IDRI-0888Open

Open the full dataset in MedSeg → All 1,010 cases - copy into your workspace to run AI and segment.

About this dataset

The Lung Image Database Consortium / Image Database Resource Initiative (LIDC-IDRI) is a public reference dataset of 1010 thoracic CT scans annotated with nodule markup from four expert radiologists per case. Originally curated by NCI/FDA/NIH from seven academic centers, it spans multiple scanner vendors (Siemens, GE, Philips, Toshiba) and reconstruction parameters - the gold standard benchmark for lung nodule detection and classification.

Real clinical scans, mixed pathology (positive + negative for nodules), multi-vendor, multi-center. The reference nodule annotations (radiologist XML markup) are not imported in v1 - use the editor to draw or copy in your own segmentations.

FactValue
Cases1,010
Series1,010
Size74.9 GB
ModalityCT
Reference masksYes
LicenseCC-BY-3.0
PublisherLIDC-IDRI Consortium (NCI/NIH/FDA)
Version2015
DOI10.7937/K9/TCIA.2015.LO9QL9SX

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.

Armato III, S. G., McLennan, G., Bidaut, L., McNitt-Gray, M. F., Meyer, C. R., Reeves, A. P., et al. (2011). The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans. Medical Physics, 38(2), 915-931.

License: CC-BY-3.0

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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