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title | Data Access |
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| 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 Type | Download all or Query/Filter |
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TCGA-LGG images - 65 subjects (DICOM, 17 GB) | | TCGA-GBM images - 102 subjects (DICOM, 32 GB) | | Segmentations - (DICOM, 4 GB) | | DCMQI Metadata (ZIP, 3.1 MB) | | TCGA key mapping (CSV) | | Please contact help@cancerimagingarchive.net with any questions regarding usage. |
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title | Detailed Description |
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| Detailed Description Collection | Statistics | Number of Studies | 168* | Number of Series | 1304 | Number of Patients | 167 | Number of Images | 1304 | Modalities | Seg | Image Size (GB) | 4 |
*For TCGA-GBM patient TCGA-06-0192, there were 2 studies. |
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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: Public collection license |
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Info |
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| Andrew Beers, Elizabeth Gerstner, Bruce Rosen, David Clunie, Steve Pieper, Andrey Fedorov, Jayashree Kalpathy-Cramer. (2018) DICOM-SEG Conversions for TCGA-LGG and TCGA-GBM Segmentation Datasets. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2018.ow6ce3ml |
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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. (2013) The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6 pp 1045-1057. DOI: 10.1007/s10278-013-9622-7 |
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). https://www.nature.com/articles/sdata2017117 |
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| Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, and Christos Davatzikos. (2017) Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.GJQ7R0EF |
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| Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, and Christos Davatzikos. (2017) Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.KLXWJJ1Q |
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 |
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| Version 1 (Current): 2020/04/30 Data Type | Download all or Query/Filter |
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TCGA-LGG images - 65 subjects (DICOM, 17 GB) | | TCGA-GBM images - 102 subjects (DICOM, 32 GB) | | Segmentations - (DICOM, 4 GB) | | DCMQI Metadata (ZIP, 3.1 MB) | | TCGA key mapping (CSV) | |
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