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Localtab Group


Localtab
activetrue
titleData Access

Data Access


not yet linked(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, 14.6 GB)


Tcia button generator
urlhttps://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/390?passcode=81eac3afc8ae271621d9fe392fd8940e501bd3c3

complete nii data on faspex


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

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Registered brain-extracted imaging converted from nii to dcm, MGMT Classifier task only. (DICOM, 11?128 GB)


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new dicom on faspex not yet linked

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

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BraTS 2021 Training set (NIfTI, 12.4 GB ID Crosswalk between BraTS ID and TCIA ID (xlsx, 79 kB)


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training data on faspex not yet linked

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

BraTS2021_MappingToTCIA



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BraTS 2021 Validation set (NIfTI, 2.2 GB)

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validation data on faspex not yet linked

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

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

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

BraTS2021_MappingToTCIA

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Click the Versions tab for more info about data releases.

Nci_crdc additional resources

  • Imaging Data Commons (IDC) (Imaging Data)
  • Click the Versions tab for more info about data releases.

    Nci_crdc additional resources

    Additional Resources for this Dataset

    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.

    TCIA Collections Used (in part) in these analyses:

    Genomic Data Commons (GDC) (Genomic, Digitized Histopathology & Clinical Data)
    Source Data TypeDownloadLicense
    Original DICOM used in BraTS 2021 Segmentation Training set from 
  • Proteomic Data Commons (PDC) (Proteomic & Clinical Data)
  • ACRIN-FMISO-Brain (ACRIN 6684)IvyGAP ,UPENN-GBM


    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/133073473/BraTS2021_TCIAderived_Seg-Task-Training.tcia?api=v2

    seg train

    Download requires the NBIA Data Retriever

    Tcia restricted license

    Original DICOM used in BraTS 2021 MGMT Classifier Training set from 

    CPTAC-GBMTCGA-GBM , IvyGAP

    Additional Resources for this Dataset

    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.

    TCIA Collections Used (in part) in these analyses:

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

    Source Data TypeDownloadLicense
    Original DICOM used in BraTS 2021 Segmentation Training set from 

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


    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/133073473/BraTS2021_TCIAderived_SegClass-Task-Training.tcia?api=v2

    seg class train

    Download requires the NBIA Data Retriever

    Tcia restricted license

    Original DICOM used in BraTS 2021 MGMT Classifier Training set from Segmentation Validation set from CPTAC-GBM TCGA-GBMTCGA-LGG , IvyGAP UPENN-GBM


    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/133073473/BraTS2021_TCIAderived_ClassSeg-Task-TrainingValidation.tcia?api=v2

    class trainseg valid


    Download requires the NBIA Data Retriever

    Tcia restricted license

    Original DICOM used in BraTS 2021 Segmentation MGMT Classifier Validation set from from 

    CPTAC-GBM TCGA-GBM ,  

    TCGA-LGG

    IvyGAP UPENN-GBM


    Tcia button generator
    urlhttps://wiki.cancerimagingarchive.net/download/attachments/133073473/BraTS2021_TCIAderived_SegClass-Task-Validation.tcia?api=v2

    seg class valid


    Download requires the NBIA Data Retriever

    Tcia restricted license

    Original

    DICOM used in BraTS 2021 MGMT Classifier Validation set from 

    CPTAC-GBMTCGA-GBM ,  IvyGAPUPENN-GBM

    imaging from UCSF-PDGM v1


    Tcia button generator
    url
    Tcia button generator
    urlhttps://wikifaspex.cancerimagingarchive.net/downloadaspera/attachmentsfaspex/133073473/BraTS2021_TCIAderived_Class-Task-Validation.tcia?api=v2

    class valid

    Download requires the NBIA Data Retriever

    Tcia restricted license

    Original imaging from UCSF-PDGM v1

    external_deliveries/383?passcode=bfd9d89cae2d79e6d824ba1a25e04fc6e37907ba


    (Download and apply the IBM-Aspera-Connect plugin to your browser to

    Tcia button generator
    urlhttps://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/383?passcode=bfd9d89cae2d79e6d824ba1a25e04fc6e37907ba
    CC BY 4.0


    Third Party Analyses of this Dataset

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




    Localtab
    titleDetailed Description

    Detailed Description

    Image Statistics

    Radiology Image Statistics

    Modalities

    MR, Segmentations

    Number of Patients

    2,040

    Number of Studies


    Number of Series

    7,131

    Number of Images

    7,131 + 400,114

    Images Size (GB)11.731


    NOTE:  The "challenge test set dataset" is sequestered on synapse.org (Project SynID: syn25829067). Please see their site 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:



    Notes about Image Registration:

    • Transformation matrices DICOM to NIfTI are not available.
    • Segmentation task image volume have been set to x=y=240 voxels by z=155 voxels.
    • All Radiogenomics Classifier task files are restored to original DICOM resolution & orientation (thus volume may vary).





    Localtab
    titleCitations & Data Usage Policy

    Citations & Data Usage Policy

    Tcia limited license policy


    Info
    titleData Citation

    Baid, U., Ghodasara, S., Mohan, S., Bilello, M., Calabrese, E., Colak, E., Farahani, K., Kalpathy-Cramer, J., Kitamura, F. C., Pati, S., Prevedello, L., Rudie, J., Sako, C., Shinohara, R., Bergquist, T., Chai, R., Eddy, J., Elliott, J., Reade, W., Schaffter, T., Yu, T., Zheng, J., Davatzikos, C., Mongan, J., Hess, C., Cha, S., Villanueva-Meyer, J., Freymann, J. B., Kirby, J. S., Wiestler, B., Crivellaro, P., Colen, R. R., Kotrotsou, A., Marcus, D., Milchenko, M., Nazeri, A., Fathallah-Shaykh, H., Wiest, R., Jakab, A., Weber, M-A., Mahajan, A., Menze, B., Flanders, A E., Bakas, S., (2023) RSNA-ASNR-MICCAI-BraTS-2021 Dataset. The Cancer Imaging Archive DOI: 10.7937/jc8x-9874 

    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
    titlePublication Citation - flagship BraTS 2021 manuscript

    Baid, U., Ghodasara, S., Mohan, S., Bilello, M., Calabrese, E., Colak, E., Farahani, K., Kalpathy-Cramer, J., Kitamura, F. C., Pati, S., Prevedello, L. M., Rudie, J. D., Sako, C., Shinohara, R. T., Bergquist, T., Chai, R., Eddy, J., Elliott, J., Reade, W., … Bakas, S. (2021). The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2107.02314

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

    , Davatzikos, C., Mongan, J., Hess, C., Cha, S., Villanueva-Meyer, J., Freymann, J. B., Kirby, J. S., Wiestler, B., Crivellaro, P., Colen, R. R., Kotrotsou, A., Marcus, D., Milchenko, M., Nazeri, A., Fathallah-Shaykh, H., Wiest, R., Jakab, A., Weber, M-A., Mahajan, A., Menze, B., Flanders, A E., Bakas, S., (2023) RSNA-ASNR-MICCAI-BraTS-2021 Dataset. The Cancer Imaging Archive DOI: 10.7937/jc8x-9874 


    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
    titlePublication Citation

    1. Baid, U., Ghodasara, S., Mohan, S., Bilello, M., Calabrese, E., Colak, E., Farahani, K., Kalpathy-Cramer, J., Kitamura, F. C., Pati, S., Prevedello, L. M., Rudie, J. D., Sako, C., Shinohara, R. T., Bergquist, T., Chai, R., Eddy, J., Elliott, J., Reade, W., Schaffter, T., Yu, T., Zheng, J., Moawad, A. W., Coelho, L. O., McDonnell, O., Miller, E., Moron, F. E., Oswood, M. C., Shih, R. Y., Siakallis, L., Bronstein, Y., Mason, J. R., Miller, A. F., Choudhary, G., Agarwal, A., Besada, C. H., Derakhshan, J. J., Diogo, M. C., Do-Dai, D D., Farage, L., Go, J. L., Hadi, M., Hill, V. B., Iv, M., Joyner, D., Lincoln, C., Lotan, E., Miyakoshi, A., Sanchez-Montano, M., Nath, J., Nguyen, X. V., Nicolas-Jilwan, M., Ortiz Jimenez, J., Ozturk, K., Petrovic, B. D., Shah, C., Shah, L. M., Sharma, M., Simsek, O., Singh, A. K., Soman, S., Statsevych, V., Weinberg, B. D., Young, R. J., Ikuta, I., Agarwal, A. K.,Cambron, S. C., Silbergleit, R., Dusoi, A., Postma, A. A., Letourneau-Guillon, L., Guzman Perez-Carrillo, G. J., Saha, A., Soni, N., Zaharchuk, G., Zohrabian, V. M., Chen, Y., Cekic, M. M., Rahman, A., Small, J. E., Sethi, V., Davatzikos, C., Mongan, J., Hess, C., Cha, S., Villanueva-Meyer, J., Freymann, J. B., Kirby, J. S., Wiestler, B., Crivellaro, P., Colen, R. R., Kotrotsou, A., Marcus, D., Milchenko, M., Nazeri, A., Fathallah-Shaykh, H., Wiest, R., Jakab, A., Weber, M-A. Mahajan ,A., Menze, B., Flanders, A. E., Bakas, S. (2021). The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification (Version 2). arXiv. DOI: 10.48550/arXiv.2107.02314


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


    Info
    titlePublication Citation

    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). DOI:  10.1109/tmi.2014.2377694


    Info
    titlePublication Citation

    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


    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

    Additional Publication Resources:

    The Collection authors suggest the below will give context to this dataset:


    You are free to use and/or refer to the BraTS datasets in your own research. 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) (Version 1) [Data set].  The Cancer Imaging Archive.  https://doi.org/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

    Other Publications Using This Data

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


    Localtab
    titleVersions

    Version 1 (Current): Updated 2023/

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    07/

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