TCIA DOIs
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  • Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach (Radiomics-Tumor-Phenotypes)

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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

Data TypeDownload all or Query/Filter
Image Data (DICOM) and Clinical Data

Please refer to each Collection page to download available images and clinical data:

NSCLC-Radiomics-Genomics (Lung3)

Gene Expression Data

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE58661

Please contact help@cancerimagingarchive.net  with any questions regarding usage.


Localtab
titleDetailed Description

Detailed Description



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 3.0) 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 acknowledge both this data set and TCIA in publications by including the following citations in your workUsers of this data must abide by the Creative Commons Attribution-NonCommercial 3.0 Unported License under which it has been published. Attribution should include references to the following citations:

Info
titleDataset Citation

Hugo J. W. L. Aerts; Emmanuel Rios Velazquez; Ralph T. H. Leijenaar; Chintan Parmar; Patrick Grossmann; Sara Cavalho; Johan Bussink; René Monshouwer; Benjamin Haibe-Kains; Derek Rietveld; Frank Hoebers; Michelle M. Rietbergen; C. René Leemans; Andre Dekker; John Quackenbush; Robert J. Gillies; Philippe Lambin. (2014). Data from: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2014..UA0JGPDG


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)

In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research:

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

Questions may be directed to help@cancerimagingarchive.net. 

Other Publications Using This Data

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


Localtab
titleVersions

Version 2 (Current): 2020/03/23

Added links to the recently published TCIA collections which reflect the additional arms of the study described in Nature Communications (http://doi.org/10.1038/ncomms5006).


Data TypeDownload all or Query/Filter
Image Data (DICOM) and Clinical Data

Please refer to each Collection page to download available images and clinical data:

NSCLC-Radiomics-Genomics (Lung3)

Gene Expression Data

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE58661

Version 1 (Current): 2016/08/02

Data TypeDownload all or Query/Filter
Image Data (DICOM)

Clinical Data (CSV, XLS)

ClinicalMetadata

Gene Expression Data



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