Summary
Put Collection Abstract here. If it's really long ask them to help you break it up such that the most important summary stuff is here and the rest goes in the Detailed Description tab.A note about available TCIA data which were converted for use in this Challenge
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. Dr. Bakas's 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, then as part of page 1 of this Agreement form TCIA needs to have the citation for the (TCGA-GBM, CPTAC-GBM, Ivy GAP, TCGA-LGG, other facial-detail-retained Collections) filled in. These earlier data that pose enough reidentification risk that TCIA must keep them behind an explicit usage agreement follow this restriction.
Acknowledgements
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.
Data Access
Note to curators! This macro is for collections that are restricted due to facial reconstruction possibility.
"DICOM and NIFTI for all imaging data, and CSV for clinical and genomic data" Clinical, Image Analyses, Image Registrations, Genomics, Software/Source Code, Radiomic Features
| Data Type | Download all or Query/Filter | License |
|---|---|---|
Images, Segmentations (NIfTI, 1.4 TB) | Complete dataset (Download and apply the IBM-Aspera-Connect plugin to your browser to retrieve this faspex package) | |
BraTS 2021 Training set in batches of XXX PatientID Images, Segmentations (NIfTI, 1.4 TB) |
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BraTS 2021 Validation set in batches of XXX PatientID Images, Segmentations (NIfTI, 1.4 TB) |
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BraTS Task2 Radiogenomics Classifier task images (DICOM?, GB) |
| ( is this open license stuff?) |
BraTS Task2 Radiogenomics Classifier task molecular marker table (JSON/XLS/CSV spreadsheet, MB) |
| ( is this open license stuff?) |
| Images from TCGA-LGG that have been transformed for use in this challenge - 108 Subjects (DICOM, 8.5 GB) |
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| Images from TCGA-GBM that have been transformed for use in this challenge- 135 subjects (DICOM, 6 GB) |
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| Images from Ivy GAP that have been transformed for use in this challenge- XXX subjects (DICOM, XX GB) | Note: Limited Access. | |
| CPTAC-GBM DICOM | ||
| UCSF-PDGM DICOM (note Evan didn't give this to us – only nifti so far) | ||
| UPENN-GBM DICOM ( others) | ||
Transformation matrices DICOM to NII (zip, XXMB) | ||
Clinical data (CSV) | ||
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. | n/a |
Click the Versions tab for more info about data releases.
Additional Resources for this Dataset
Note to curators! Use this any time you are linking to NCI's IDC/GDC/PDC resources. The links below are examples and will need to be tailored to point to the specific dataset (see parameters in URLS).
Additional Resources for this Dataset
The NCI Cancer Research Data Commons (CRDC) provides access to additional data and a cloud-based data science infrastructure that connects data sets with analytics tools to allow users to share, integrate, analyze, and visualize cancer research data.
- Imaging Data Commons (IDC) (Imaging Data)
- Proteomic Data Commons (PDC) (Proteomic & Clinical Data)
- Genomic Data Commons (GDC) (Genomic & Clinical Data)
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
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:
- <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>
Detailed Description
Image Statistics | Radiology Image Statistics | Pathology Image Statistics |
|---|---|---|
Modalities | ||
Number of Patients | ||
Number of Studies | ||
Number of Series | ||
Number of Images | ||
| Images Size (GB) |
<< Add any additional information that didn't fit or belong in the Summary section. >>
Citations & Data Usage Policy
Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:
Data Citation
DOI goes here. Create using Datacite with information from Collection Approval form
Publication Citation
U.Baid, et al., "The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification", arXiv:2107.02314, 2021.
Acknowledgement
Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary.
TCIA 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.
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. >>