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  • Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection (BraTS-TCGA-LGG)

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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
Images - 108 Subjects (DICOM, 8.5 GB)

Processed images with segmentations and radiomic features - 65 subjects (NIFTI, 536 MB)

BRATS 2018 Test Data Set - 43 subjects (NIFTI, 366 MB)

Please contact the helpdesk to request access to these files.

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


Localtab
titleDetailed Description

Detailed Description

Data resulting from this experiment is available in the following formats:

  • DICOM image format
  • Processed NIFTI images with segmentations and radiomic features


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. 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 work:

Info
titleData Citation

Spyridon Bakas S, Hamed Akbari H, Aristeidis Sotiras A, Michel Bilello M, Martin Rozycki M, Justin Kirby J, John Freymann J, Keyvan Farahani K, and Christos Davatzikos C. (2017) Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection [Data Set]. The Cancer Imaging Archive. https://doi.org/DOI:  10.7937/K9/TCIA.2017.GJQ7R0EF


Info
titlePublication Citation

Bakas S, Akbari H, Sotiras A, Bilello M, Rozycki M, Kirby J, Freymann J, Farahani K, Davatzikos C. (2017) Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Nature Scientific Data, 4:170117 DOI: 10.1038/sdata.2017.117


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

Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Michel Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, Christos Davatzikos. "Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features", Nature Scientific Data, 4:170117 doi: 10.1038/sdata.2017.117 (2017).

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 1 (Current): 2017/07/17

Data TypeDownload all or Query/Filter
Images - 108 subjects (DICOM, 8.5 GB)

Processed images with segmentations and radiomic features - 65 subjects (NIFTI, 536 MB)

BRATS 2018 Test Data Set - 43 subjects (NIFTI, 366 MB)

Please contact the helpdesk to request access to these files.



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