---
license: cc-by-4.0
task_categories:
- image-segmentation
tags:
- medical
- ct
- lung
- nodule
- luna16
pretty_name: LUNA16 — LUng Nodule Analysis 2016
size_categories:
- 100<n<1K
configs:
- config_name: default
  data_files:
  - split: preview
    path: data/preview-*
dataset_info:
  features:
  - name: patient_id
    dtype: string
  - name: subset
    dtype: string
  - name: num_slices
    dtype: int32
  - name: has_nodule_in_mid_slice
    dtype: bool
  - name: image
    dtype: image
  - name: lung_mask
    dtype: image
  - name: nodule_mask
    dtype: image
  - name: overlay
    dtype: image
  splits:
  - name: preview
    num_bytes: 317991662
    num_examples: 888
  download_size: 316899869
  dataset_size: 317991662
---

# LUNA16

A mirror of the LUNA16 (LUng Nodule Analysis 2016) challenge data — 888 thoracic
LDCT scans derived from LIDC-IDRI — repackaged for use in the EasyMedSeg
medical segmentation framework.

## Contents
- `subset0/` … `subset9/` — 888 CT scans in MetaImage format (`.mhd` + `.raw`)
- `seg-lungs-LUNA16/` — official lung-field masks (`.mhd` + `.zraw`)
- `nodule-masks-spheres/` — derived nodule masks built from `annotations.csv`
  by drawing a sphere of `diameter_mm` at each nodule centroid.
- `annotations.csv` — 1,186 nodule annotations (centroid + diameter)
- `candidates.csv`, `candidates_V2.csv` — false-positive-reduction candidates
- `sampleSubmission.csv` — challenge submission template

## Mask sources

LUNA16 ships **only** centroid+diameter annotations for nodules — there are no
official voxel-level nodule masks. Two derived mask sources are provided here:

1. **Lung-field masks** (`seg-lungs-LUNA16/`) — official, paired 1:1 with all
   888 scans. Per the original release: *"provided to aid nodule detection;
   NOT intended as the reference standard for any segmentation study."*
2. **Nodule sphere masks** (`nodule-masks-spheres/`) — generated by the
   uploader from `annotations.csv`: for each scan, a binary uint8 volume with
   a sphere of `diameter_mm` placed at each nodule centroid. Use as an
   approximate target for nodule segmentation; not a true voxel-level GT.

## Source
- Zenodo Part 1: https://zenodo.org/records/3723295 (subsets 0–6, masks, annotations)
- Zenodo Part 2: https://zenodo.org/records/4121926 (subsets 7–9)
- Challenge homepage: https://luna16.grand-challenge.org/

## License
CC BY 4.0 — same as the original Zenodo release.

## Citation
> Setio, A.A.A., Traverso, A., de Bel, T., Berens, M.S.N., et al. (2017).
> **Validation, comparison, and combination of algorithms for automatic detection
> of pulmonary nodules in computed tomography images: The LUNA16 challenge.**
> *Medical Image Analysis* 42: 1–13.
> doi:10.1016/j.media.2017.06.015