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Localtab Group


Localtab
activetrue
titleData Access

Data Access

Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.

Data TypeDownload all or Query/Filter
Images, Segmentations, and Radiation Therapy Structures (DICOM, 29GB)

 

(Requires the NBIA Data Retriever.)

Lung1 clinical (CSV)

Click the Versions tab for more info about data releases.

Third Party Analyses of this Dataset

TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:


Localtab
titleDetailed Description

Detailed Description

Collection Statistics


Modalities

CT, RTSTRUCT, SEG

Number of PatientsParticipants

422

Number of Studies

844

Number of Series

1265

Number of Images

52072

Image Size (GB)29.3

Radiation Oncologist Tumor Segmentations

The RTSTRUCT files in this data contain a manual delineation by a radiation oncologist of the 3D volume of the primary gross tumor volume ("GTV-1"). 

For viewing quickly we recommend Dicompyler (http://www.dicompyler.com/) which is an open source, cross-platform DICOM RT viewer.  Slicer has a SlicerRT module (http://slicerrt.github.io/index.html) which enables use of this kind of data.  The Radiotherapy DICOM toolkit may also be useful for working with this data (https://github.com/dicom/rtkit).

Clinical Data

Corresponding clinical data can be found here: Lung1.clinical.csv.

Please note that survival time is measured in days from start of treatment. DICOM patients names are identical in TCIA and clinical data file.


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

This collection may not be used for commercial purposes. It is available to browse, download, as outlined in the Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0https://creativecommons.org/licenses/by-nc/3.0/.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net

Please be sure to include the following citations in your work if you use this data set:

Info
titleData Citation

Aerts, H. J. W. L., Wee, L., Rios Velazquez, E., Leijenaar, R. T. H., Parmar, C., Grossmann, P., … Lambin, P. (2019). Data From NSCLC-Radiomics [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.PF0M9REI


Info
titlePublication Citation

Aerts, H. J. W. L., Velazquez, E. R., Leijenaar, R. T. H., Parmar, C., Grossmann, P., Cavalho, S., … Lambin, P. (2014, June 3). Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature Communications. Nature Publishing Group. http://doi.org/10.1038/ncomms5006  (link)


Info
titleTCIA Citation

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper)

Other Publications Using This Data

TCIA maintains a list of publications that leverage our data. If you have a publication you'd like to add, please contact the TCIA Helpdesk.


Localtab
titleVersions

Version 3 (Current): Updated 2019/10/23

Data TypeDownload all or Query/Filter
Images (DICOM, 29GB)

 

(Requires the NBIA Data Retriever.)

Lung1 clinical (CSV)

  • Re-checked and updated the RTSTRUCT files to amend issues in the previous submission due to missing RTSTRUCTS or regions of interest that were not vertically aligned with the patient image.
  • In 4 cases (LUNG1-083,LUNG1-095,LUNG1-137,LUNG1-246) re-submitted the correct CT images.
  • The regions of interest now include the primary lung tumor labelled as “GTV-1”, as well as organs at risk.
  • For one case (LUNG1-128) the subject does not have GTV-1 because it was actually a post-operative case; we retained the CT scan here for completeness.
  • Added DICOM SEGMENTATION objects to the collection, which makes it easier to search and retrieve the GTV-1 binary mask for re-use in quantitative imaging research.
  • Clinical data updated as follow-up time has been extended.

Version 2: Updated 2016/05/31

Data TypeDownload all or Query/Filter
Images (DICOM, 25GB)

 

(Requires the NBIA Data Retriever.)

Lung1 clinical (CSV)

 Added 318 RTSTRUCT files for existing subject imaging data

Version 1: Updated 2014/07/02

Data TypeDownload all or Query/Filter
Images (DICOM, 25GB)
Lung1 clinical (CSV)




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