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Dr. Bakas's group has provided skull-stripped challenge TRAINING data in NIfTI that do not pose DUA-level risk of potential facial reidentification, and segmentations to go with them. This group has provided the skull-stripped challenge TEST data in NIfTI, and segmentations to go with them, available upon request through the helpdesk. If you want the DICOM-format files, then as part of page 1 of this Agreement form TCIA needs to have the citation(s) for the (TCGA-GBM, CPTAC-GBM, Ivy GAP, TCGA-LGG, other facial-detail-retained CollectionsUPENN-GBM, UCSF-PDGM, ACRIN-FMISO-Brain) filled in. These earlier data that pose enough reidentification risk that TCIA must keep them behind an explicit usage agreement follow this restriction.
Please also note that specificity of the exact series in DICOM became which exact volume in NIfTI has, unfortunately, been lost to time but the available lists below (in most cases, by Collection, TCIA Patient ID, Study date) represent our best effort at reconstructing the BraTS input imaging.

...

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.

  • Continue with any names from additional submitting sites if collection consists of more that one.
    Copied from Kaggle site: "Data used in this publication were obtained as part of the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge Data used in this publication were obtained as part of the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge project through Synapse ID (syn25829067).

Localtab Group


Localtab
activetrue
titleData Access

Data Access

Tcia license 4 international

Note to curators! This macro is for collections that are restricted due to facial reconstruction possibility.

Tcia head license access



NIfTI derived from CPTAC-GBM sources
  • (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    Data TypeDownload all or Query/FilterLicense

    Images and Segmentations (NIfTI, 1.4 TB)


    Complete dataset all tasks

    Tcia button generator

    complete data on faspex


    (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    Tcia cc by 4







    BraTS 2021 Segmentation  Segmentation Training set in batches of XXX PatientID Images, Segmentations ((NIfTI, XX GB )



    1. batch1 (ID PP to QQ) (XX GB) - (CPTAC GBM)processed from ACRIN-FMISO-Brain) 

      Tcia button generator

      batch1


    2. batch2 (ID XX to YY) (XX GB) (TCGA-LGG) processed from CPTAC GBM)

      Tcia button generator

      batch2


    3.  (and so onbatch3 (processed from IvyGAP)

    4. batch4 (processed from TCGA-GBM)

    5. batch5 (processed from TCGA-LGG)
    6. batch6 (processed from UPENN-GBM)
    7. batch7 (processed from UCSF-PDGM)

      (Download and apply the
      IBM-(Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    Tcia cc by 4

    BraTS 2021 Segmentation Validation set in batches of XXX PatientID Images, (maybe not Segmentations?)  (NIfTI, 1.4 TB)XX GB)

      1. batch1 (processed from CPTAC GBM)

      2. batch2 (processed from IvyGAP)
      3. batch3 (processed from TCGA-GBM)

      4. batch4 (processed from TCGA-LGG)
      5. batch5 (processed from UPENN-GBM)
      6. batch6 (processed from UCSF-PDGM)
    1. Tcia button generator

      NIfTI derived from Ivy GAP sources

    Tcia button generator

    Tcia cc by 4

    BraTS 2021 Segmentation Validation set in batches of XXX PatientID  Segmentations  (NIfTI, 1.4 TB)Validation 

    Brand new data files not elsewhere on TCIA


    (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    TCIA Restricted (special permission beyond defacing DUA required to be fleshed out later)

    BraTS 2021 Segmentation Task Training 
    Brand new data files not elsewhere on TCIA


    (Download and apply

    the 

    the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    CC by 4.0




    BraTS Task2 Radiogenomics Classifier task Training images (DICOM, GB)

    1. link to faspex for nifti
    2. link to GDC/PDC if the detail are there ( e.g. TCGA)
    3. dicom-->nifti→dicom also on Faspex

    ( is this open license stuff?)

    BraTS Task2 Radiogenomics Classifier task molecular marker table (JSON/XLS/CSV spreadsheet, MB)

    1. download JSON/XLS/CSV spreadsheet  or 
    2. if external link that would go below not in this table

    ( is this open license stuff?)

    BraTS 2021 Classifier Training Task
    Brand new data files not elsewhere on TCIA

    (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) 

    CC by 4.0




    Complete training ( highest faspex folder) 
        ( folder of BRats2021-CPTAC-GBM) involved in Seg task training 
        ( folder of Brats2021-TCGA-GBM) involved in seg task training
        


    complete validation involved in classifier from xx collection forms a batch here) 










    Clinical data (CSV)



    Tcia button generator



    Tcia cc by 4

    Tcia restricted license

    Feature matrices (format, ##GB)

    link or attachment

    Tcia cc by 4

    Click the Versions tab for more info about data releases.

    Additional Resources for this Dataset

    Nci_crdc additional resources

    Note to curators! Below are examples for what to do with other external resources/links that don't fit into the above categories.

    The following external resources have been made available by the data submitters.  These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.

    • Software / Code on Github
    • Genomics data in DbGAP
    • Genomics data in Gene Expression Omnibus
    • RSNA or kaggle link to molecular marker table if they only provide us a link

    ID Crosswalk between BraTS ID and TCIA ID (xlsx, 79 kB)


    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/133073473/BraTS2021_MappingToTCIA.xlsx?api=v2

    BraTS2021_MappingToTCIA



    Tcia cc by 4

    Click the Versions tab for more info about data releases.

    Additional Resources for this Dataset

    Nci_crdc additional resources


    Note to curators! Below are examples for what to do with other external resources/links that don't fit into the above categories.

    The following external resources have been made available by the data submitters.  These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.

    • Software / Code on Github
    • Genomics data in DbGAP
    • Genomics data in Gene Expression Omnibus
    • RSNA or kaggle link to molecular marker table if they only provide us a link

    TCIA Collections Used TCIA Collections Used (in part) in these analyses:

    Source Data TypeDownloadLicense
    DICOM Used in BraTS 2021 Segmentation Training set from 

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    UPENN-GBM

    DICOM Used in BraTS 2021 Classifier Training set from CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,


    Note: Limited Access.


    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    DICOM Used in BraTS 2021
    Segmentation Validation
    Classifier Training set from 

    CPTAC-GBMTCGA-GBM ,

     TCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    IvyGAPUPENN-GBM

    Tcia restricted license

    To get data used in BraTS-

    To get data used in BraTS-

    2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    DICOM Used in BraTS 2021
    Classifier
    Segmentation Validation set from 

    CPTAC-GBMTCGA-GBMTCGA-LGG

    ACRIN-FMISO-Brain (ACRIN 6684)

    IvyGAP

    IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    UPENN-GBM

    Tcia restricted license

    To get data used in BraTS-2021 please request the

    To get data used in BraTS-2021 please request the

    following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    UCSF-PDGM  DICOM

    Data retriever or Faspex?

    Tcia cc by 4

    UPENN-GBM DICOM

    Data retriever or Faspex?

    Tcia cc by 4

    Images from TCGA-LGG that have been transformed for use in this challenge  - 108 Subjects (DICOM, 8.5 GB) Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/24282668/doiJNLP-JAMS4RFq.tcia?api=v2
    DICOM Used in BraTS 2021 Classifier Validation set from 

    CPTAC-GBMTCGA-GBM ,  IvyGAPUPENN-GBM

    TCGA-LGG batch1 source series

    Note: Limited Access.

    Click the Download  button to save a ".tcia" manifest file to your computer, which you must open with the  

    Download requires the NBIA Data Retriever

     

    Tcia restricted license

    Images from TCGA-GBM that have been transformed for use in this challenge- 135 subjects (DICOM, 6 GB)
    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/24282666/doiJNLP-QoOaKUdn.tcia?api=v2

    TCGA-GBM batch1 source series

    Note: Limited Access.
    Click the Download  button to save a ".tcia" manifest file, needs the NBIA Data Retriever

    Tcia restricted license

    Images from Ivy GAP that have been transformed for use in this challenge- XXX subjects (DICOM, XX GB)
    Tcia button generator

    Ivy GAP batch1 source series

    Note: Limited Access.
    Click the Download  button to save a ".tcia" manifest file, needs the  NBIA Data Retriever

    Tcia restricted license

    Third Party Analyses of this Dataset

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP













    UCSF-PDGM  nonDICOM. New package?

    Data retriever or Faspex?

    Tcia cc by 4











    Third Party Analyses of this Dataset

    TCIA encourages the community TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:

    • <these get filled in as groups cite the dataset in their papers related to analysis of the 2021 task 1 & task2 using this Collection's DOI>



    •  the "challenge test set dataset" is sequestered on synapse as a tarball of nii & seg & age & diagnosis. Not available. Please see <website> for more detail.

    The data used in BraTS Challenges often have some overlap with other TCIA Collections, cases, and series. Some filters for handling these, so that you can work with statistically not-duplicated images, include these below:

    Localtab
    titleDetailed Description

    Detailed Description

    Image Statistics

    Radiology Image StatisticsPathology Image Statistics

    Modalities



    Number of Patients



    Number of Studies



    Number of Series



    Number of Images



    Images Size (GB)


    •  the "challenge test set dataset" is sequestered on synapse as a tarball of nii & seg & age & diagnosis. Not available. Please see <website> for more detail.

    The data used in BraTS Challenges often have some overlap with other TCIA Collections, cases, and series. Some filters for handling these, so that you can work with statistically not-duplicated images, include these below:

    Localtab
    titleDetailed Description

    Detailed Description

    Image Statistics

    Radiology Image StatisticsPathology Image Statistics

    Modalities

    Number of Patients

    Number of Studies

    Number of Series

    Number of Images

    Images Size (GB)
    Source Data TypeDownloadLicense
    DICOM Used in BraTS 2021 Segmentation Training set from 

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    DICOM Used in BraTS 2021 Classifier Training set from 

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    DICOM Used in BraTS 2021 Segmentation Validation set from 

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    DICOM Used in BraTS 2021 Classifier Validation set from 

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,

    Note: Limited Access.
    Download requires the NBIA Data Retriever

    Tcia restricted license

    To get data used in BraTS-2021 please request the following Collections in your Agreement:

    CPTAC-GBMTCGA-GBMTCGA-LGGACRIN-FMISO-Brain (ACRIN 6684)IvyGAP

    UCSF-PDGM  DICOM

    Data retriever or Faspex?

    Tcia cc by 4

    UPENN-GBM DICOM

    Data retriever or Faspex?

    Tcia cc by 4

    Images from TCGA-LGG that have been transformed for use in this challenge  - 108 Subjects (DICOM, 8.5 GB)
    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/24282668/doiJNLP-JAMS4RFq.tcia?api=v2

    TCGA-LGG batch1 source series

    Note: Limited Access.
    Click the Download  button to save a ".tcia" manifest file to your computer, which you must open with the  NBIA Data Retriever 

    Tcia restricted license

    Images from TCGA-GBM that have been transformed for use in this challenge- 135 subjects (DICOM, 6 GB)
    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/24282666/doiJNLP-QoOaKUdn.tcia?api=v2

    TCGA-GBM batch1 source series

    Note: Limited Access.
    Click the Download  button to save a ".tcia" manifest file, needs the NBIA Data Retriever

    Tcia restricted license

    Images from Ivy GAP that have been transformed for use in this challenge- XXX subjects (DICOM, XX GB)
    Tcia button generator

    Ivy GAP batch1 source series

    Note: Limited Access.
    Click the Download  button to save a ".tcia" manifest file, needs the  NBIA Data Retriever

    tcia-restricted-license


    Note: Transformation matrices DICOM to NIfTI are not available. Seg tasks are x/y/z 240/240/155 and all Radiogenomics Classifier files are restored to original DICOM resolution & orientation.



    Localtab
    titleCitations & Data Usage Policy

    Citations & Data Usage Policy

    Tcia limited license policy

    Info
    titleData Citation

    DOI goes here. Create using Datacite with information from Collection Approval form

    44 authors, most with ORCiD. 



    Info
    titlePublication Citation

    U.Baid, et al., The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification arXiv:2107.02314, 2021. 


    Info
    titleAcknowledgement

    "The results <published or shown> here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/."



    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. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC.https://doi.org/10.1007/s10278-013-9622-7

    Other Publications Using This Data

    TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

    Copied from the Kaggle site: 

    You are free to use and/or refer to the BraTS datasets in your own research, provided that you always cite the flagship manuscript (published or pre-published) resulting from the challenge as well as the following three manuscripts:

    1.  Baid, U., et al., The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification, arXiv:2107.02314, 2021.
    2. Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., Lanczi, L., Gerstner, E., Weber, M.-A., Arbel, T., Avants, B. B., Ayache, N., Buendia, P., Collins, D. L., Cordier, N., … Van Leemput, K. (2015). The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). In IEEE Transactions on Medical Imaging (Vol. 34, Issue 10, pp. 1993–2024). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/tmi.2014.2377694
    3. 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. In Scientific Data (Vol. 4, Issue 1). https://doi.org/10.1038/sdata.2017.117

      In addition, please be specific and also cite the following datasets that were part of this Challenge:
      1. 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
      2. 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
      3. Scarpace, L., Mikkelsen, T., Cha, S., Rao, S., Tekchandani, S., Gutman, D., Saltz, J. H., Erickson, B. J., Pedano, N., Flanders, A. E., Barnholtz-Sloan, J., Ostrom, Q., Barboriak, D., & Pierce, L. J. (2016). The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.RNYFUYE9
      4. Pedano, N., Flanders, A. E., Scarpace, L., Mikkelsen, T., Eschbacher, J. M., Hermes, B., Sisneros, V., Barnholtz-Sloan, J., & Ostrom, Q. (2016). The Cancer Genome Atlas Low Grade Glioma Collection (TCGA-LGG) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.L4LTD3TK
      5. Calabrese, E., Villanueva-Meyer, J., Rudie, J., Rauschecker, A., Baid, U., Bakas, S., Cha, S., Mongan, J., & Hess, C. (2022). The University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) [Dataset].  The Cancer Imaging Archive.  https://10.7937/tcia.bdgf-8v37 
      6. Bakas, S., Sako, C., Akbari, H., Bilello, M., Sotiras, A., Shukla, G., Rudie, J. D., Flores Santamaria, N., Fathi Kazerooni, A., Pati, S., Rathore, S., Mamourian, E., Ha, S. M., Parker, W., Doshi, J., Baid, U., Bergman, M., Binder, Z. A., Verma, R., … Davatzikos, C. (2021). Multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients from the University of Pennsylvania Health System (UPENN-GBM) (Version 2) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.709X-DN49


    Localtab
    titleVersions

    Version X (Current): Updated yyyy/mm/dd

    copy Access tab table here

    << One or two sentences about what you changed since last version.  No note required for version 1. >> 


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