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title | Data Access |
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| Data AccessClick the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever Data Type | Download all or Query/Filter |
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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 |
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title | Detailed Description |
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| Detailed DescriptionData resulting from this experiment is available in the following formats: - DICOM image format
- Processed NIFTI images with segmentations and radiomic features
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Localtab |
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title | Citations & Data Usage Policy |
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| 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 |
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| 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 |
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title | Publication Citation |
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| 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
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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) |
In addition to the dataset citation above, please be sure to cite the following if you utilize these data in your research: Info |
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title | Publication Citation |
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| 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 DataTCIA 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 |
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| Version 1 (Current): 2017/07/17Data Type | Download all or Query/Filter |
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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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