Data AccessClick 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 Type | Download all or Query/Filter |
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Images (DICOM, 29GB) | | Lung1 clinical (CSV) | |
Click the Versions tab for more info about data releases. |
Detailed Description | |
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Modalities | CT, RTSTRUCT, SEG | Number of Patients | 422 | Number of Studies | 844 | Number of Series | 1265 | Number of Images | 52072 | Image Size (GB) | 29.3 |
Radiation Oncologist Tumor SegmentationsThe 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 DataCorresponding 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. |
Citations & Data Usage Policy This collection may not be used for commercial purposes. This collection is freely available to browse, download, as outlined in the Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) https://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: 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 |
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) |
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 DataTCIA maintains a list of publications that leverage our data. If you have a publication you'd like to add, please contact the TCIA Helpdesk. |
Version 3 (Current): Updated 2019/10/23Data Type | Download all or Query/Filter |
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Images (DICOM, 29GB) | | 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 2016/05/31Data Type | Download all or Query/Filter |
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Images (DICOM, 25GB) | | Lung1 clinical (CSV) | |
Added 318 RSTRUCT files for existing subject imaging data Version 1: Updated 2014/07/02Data Type | Download all or Query/Filter |
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Images (DICOM, 25GB) | | Lung1 clinical (CSV) | |
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