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  • DICOM-SEG Conversions for TCGA-LGG and TCGA-GBM Segmentation Datasets (DICOM-Glioma-SEG)

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Localtab Group



Localtab
activetrue
titleData Access

Data Access

Tcia head license 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/FilterLicense
TCGA-LGG images - 65 subjects (DICOM, 17 GB)

Tcia restricted license

TCGA-GBM images - 102 subjects (DICOM, 32 GB)

Tcia restricted license

Segmentations -  (DICOM, 4 GB)
Tcia restricted license


DCMQI Metadata (ZIP, 3.1 MB)

Tcia cc by 4

TCGA key mapping (CSV)

Tcia cc by 4


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:




Localtab
titleDetailed Description

Detailed Description


CollectionStatistics

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.




Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Tcia limited license policy

Info
titleData Citation

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


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. (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:


Info
titlePublication Citation

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


Info
titleData Citation

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


Info
titleData Citation

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 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): 2020/04/30


Data TypeDownload all or Query/Filter
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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