Skip to content

TCIA NSCLC-Radiomics: 422 lung-cancer CTs with RTSTRUCT and SEG contours (DICOM)

pl.load("tcia_nsclc_radiomics_dicom") loads this dataset. The original DICOM release of the Lung1 cohort (see hf_nsclc_radiomics for the NIfTI conversion): planning CT, the radiotherapy structure set (GTV, lungs, heart, oesophagus, spinal cord) and a DICOM SEG per patient. Series are listed through the public NBIA API (no account) and each one is downloaded as a zip of DICOM files on first access; the folder is then a DICOM volume (LPS mm from the headers).

import pardesline as pl

ds = pl.load("tcia_nsclc_radiomics_dicom")
print(ds.describe())  # roles, frames, units, labels, licence, citation
s = ds[0]
obj = s.ct  # fetched now, cached under ~/.cache/pardesline/datasets/tcia_nsclc_radiomics_dicom

Provenance and licence
Source The Cancer Imaging Archive, collection NSCLC-Radiomics through the NBIA REST API
Scheme tcia
Size of the whole source 32.2 GB
Licence CC-BY-3.0
Commercial use allowed by the licence
Redistribution allowed
Licence note CC BY 3.0 on the TCIA collection page (checked 2026-10-14).
Terms https://www.cancerimagingarchive.net/collection/nsclc-radiomics/
Homepage https://www.cancerimagingarchive.net/collection/nsclc-radiomics/
Cite Aerts H.J.W.L., Wee L., Rios Velazquez E., et al. Data From NSCLC-Radiomics (version 4). The Cancer Imaging Archive, 2019. doi:10.7937/K9/TCIA.2015.PF0M9REI. Clark K., Vendt B., Smith K., et al. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. J Digit Imaging 26(6):1045-1057, 2013.
Samples grouped by id

Roles (what each sample contains)

Role Type Frame Units Labels / layout Pattern or file
ct volume (CT) from the file header from the file header {id}/CT/{series}
Planning CT, DICOM series
rtstruct file from the file header from the file header {id}/RTSTRUCT/{series}
RTSTRUCT contours (GTV-1, lungs, heart, oesophagus, spinal cord)
seg file from the file header from the file header {id}/SEG/{series}
DICOM SEG of the same structures

Standardized layout

Files are fetched on first access into the dataset cache and stay in their original format; ds.export(folder) writes every sample as standard files (PLY for points and meshes, MetaImage for volumes and label maps) with a .pardesline.json sidecar carrying frame, units, labels, licence and provenance, plus a manifest for the folder. Label maps become exact surfaces with to_mesh(label=k), DICOM series become one volume, raw arrays are decoded through the layout above.

ds = pl.load("tcia_nsclc_radiomics_dicom").take(2)
ds.export("./standardized")        # PLY / MetaImage + sidecars + manifest.json

Algorithms and models that run on it

Generated from src/pardesline/data/manifests/tcia_nsclc_radiomics_dicom.json on 2026-10-14.