Localtab |
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title | Detailed Description |
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| 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. |
Localtab |
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title | Citations & Data Usage Policy |
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| 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 3.0) 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: Info |
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| 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 |
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title | Publication Citation |
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| 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 |
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| 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. |
Localtab |
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| 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 RTSTRUCT 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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