---
license: cc-by-3.0
task_categories:
- image-segmentation
tags:
- medical
- ct
- thoracic
- lung
- radiotherapy
- oar
- dicom
- rtstruct
size_categories:
- n<1K
dataset_info:
  features:
  - name: patient_id
    dtype: string
  - name: institution
    dtype: string
  - name: num_slices
    dtype: int32
  - name: middle_z
    dtype: int32
  - name: classes_present
    list: string
  - name: middle_slice
    dtype: image
  - name: middle_mask
    dtype: image
  - name: middle_overlay
    dtype: image
  splits:
  - name: train
    num_bytes: 8692471
    num_examples: 36
  - name: test_offsite
    num_bytes: 3015476
    num_examples: 12
  - name: test_online
    num_bytes: 2868798
    num_examples: 12
  download_size: 14561146
  dataset_size: 14576745
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test_offsite
    path: data/test_offsite-*
  - split: test_online
    path: data/test_online-*
---

# LCTSC — Lung CT Segmentation Challenge 2017 (AAPM)

Mirror of the [TCIA LCTSC collection](https://www.cancerimagingarchive.net/collection/lctsc/) for the AAPM 2017 Thoracic Auto-segmentation Grand Challenge. 60 thoracic CT cases (CT volumes + DICOM RTSTRUCT contours) covering five organs at risk for radiation treatment planning.

## Classes (5 OARs)

| Class | Notes |
| --- | --- |
| Esophagus | |
| Heart | |
| Left Lung | RTSTRUCT splits Lungs into L/R |
| Right Lung | |
| Spinal Cord | |

## Splits

| Split | Cases | HF folder |
| --- | --- | --- |
| Training | 36 | `train/` |
| Off-site test | 12 | `test_offsite/` |
| Online (live) test | 12 | `test_online/` |
| **Total** | **60** | |

Cases are stratified across three institutions (S1: MD Anderson, S2: MSKCC, S3: MAASTRO) — case IDs encode the institution: e.g., `LCTSC-Train-S2-005`.

## Data layout

Each patient folder contains:
- one CT series (`<study_uid>/<series_uid>/*.dcm`, ~140 slices, 512×512, ~512 KB/slice)
- one DICOM RTSTRUCT (`<study_uid>/<small_uid>/1-1.dcm`, ~2 MB) with the five OAR contours

```
train/LCTSC-Train-S1-001/<study>/<ct_series>/*.dcm
train/LCTSC-Train-S1-001/<study>/<rtstruct_series>/*.dcm
```

## License & citation

Released under **CC BY 3.0** by TCIA.

When using this data, cite the original publication and TCIA per [the LCTSC citation policy](https://www.cancerimagingarchive.net/collection/lctsc/):

> Yang J, Veeraraghavan H, Armato SG III, et al. Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017. Med Phys. 2018;45(10):4568-4581. doi:10.1002/mp.13141

> Clark K, Vendt B, Smith K, et al. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. J Digit Imaging. 2013;26(6):1045-1057.

Original DOI: [10.7937/K9/TCIA.2017.3R3FVZ08](https://doi.org/10.7937/K9/TCIA.2017.3R3FVZ08).