Published October 2025 | Version v1

NLSTSeg: Expert lesion segmentations and radiomics features for NLST CT images

  • 1. ROR icon Brigham and Women's Hospital
  • 2. Brigham and Women's Hospital Department of Radiology

Description

This collection contains expert volumetric segmentations of the suspicious lesions in the NLST collection [1] CT images along with the radiomics features extracted from the segmented regions. 

The annotations in this dataset were collected and shared by the authors as part of the activities described in [2]. The annotations were originally stored in NIfTI format, and shared via Zenodo [3]. This dataset contains the annotations harmonized into DICOM representation. This dataset further enriches the segmentations by including first-order (e.g., region signal intensity measurements) and shape (e.g., volume and surface area) features extracted using pyradiomics. 

This dataset is available from the NCI Imaging Data Commons (IDC), and can be explored interactively in the IDC Portal using this link: https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=NLSTSeg

Specific files included in the record are available via the following. The suffix of the manifest indicates its content, which is the list of pointers to the public Google Cloud Storage (GCS) or Amazon Web Services (AWS) buckets containing the files included in the collection:

    1. -gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).

    2. -aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).

    3. -dcf.dcf: Gen3-based manifest (see details in https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids). 

[1] National Lung Screening Trial Research Team. (2013). Data from the National Lung Screening Trial (NLST) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.HMQ8-J677

[2] Chen, K.-H., Lin, Y.-H., Wu, S., Shih, N.-W., Meng, H.-C., Lin, Y.-Y., Huang, C.-R. & Huang, J.-W. NLSTseg: A pixel-level lung cancer dataset based on NLST LDCT images. Sci. Data 12, 1475 (2025). https://doi.org/10.1038/s41597-025-05742-x 

[3] Lin, Y. (2025). NLSTseg: A Pixel-level Lung Cancer Dataset Based on NLST LDCT Images [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14838349

Files

Files (313.0 kB)

Name Size Download all
md5:20a62088a50fbcabd19fedcef4faa14f
115.8 kB Download
md5:db4cb177b14f0cbed01e55900ef0b3fe
81.5 kB Download
md5:84ea989f5dee49f22f7d5b213ee7ff0e
115.8 kB Download

Additional details

Related works

Is derived from
Dataset: 10.7937/TCIA.HMQ8-J677 (DOI)
Dataset: 10.5281/zenodo.14838349 (DOI)
Is described by
Publication: 10.1038/s41597-025-05742-x (DOI)
Is published in
Other: 10.25504/FAIRsharing.0b5a1d (DOI)