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title | Data Access |
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| Data Access
Be sure to "request dataset" with these : DICOM-Glioma-SEG, TCGA-GBM, and TCGA-LGG in your Agreement on page 1 so that we can process your request efficiently. Complete all pages. 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 | License |
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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. Collections Used in this Third Party Analysis Below is a list of the Collections used in these analyses: |
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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 Tcia limited license policy |
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| Beers, A., Gerstner, E., Rosen, B., Clunie, D., Pieper, S., Fedorov, A., & Kalpathy-Cramer, J. (2018). DICOM-SEG Conversions for TCGA-LGG and TCGA-GBM Segmentation Datasets [Data set]. 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, 26(6), 1045–1057. https://doi.org/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:
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title | Publication Citation |
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| Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J. S., Freymann, J. B., Farahani, K., & Davatzikos, C. (2017). Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Scientific Data, 4(1). https://doi.org/10.1038/sdata.2017.117 https://www.nature.com/articles/sdata2017117 |
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| Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J., Freymann, J., Farahani, K., & Davatzikos, C. (2017). Segmentation Labels for the Pre-operative Scans of the TCGA-LGG collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.GJQ7R0EF |
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| Bakas, S., Akbari, H., Sotiras, A., Bilello, M., Rozycki, M., Kirby, J., Freymann, J., Farahani, K., & Davatzikos, C. (2017). Segmentation Labels for the Pre-operative Scans of the TCGA-GBM collection [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2017.KLXWJJ1Q |
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. |
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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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