| --- |
| 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). |
|
|
