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Summary

This collection

 

In addition to the DICOM images, this collection also contains.

This data set was provided to TCIA by Authors: Bradley Erickson, Zeynettin Akkus, Jiri Sedlar, Panagiotis Korfiatis.  

 

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.

Data TypeDownload all or Query/Filter
Images (DICOM, XXX GB)
 
Segmentations (NiFTI)

Click the Versions tab for more info about data releases.

Detailed Description

Collection Statistics

Updated 2017/07/31

Modalities

MRI, SEG, NIfTI

Number of Patients

159

Number of Studies

160

Number of Series

319

Number of Images

17360

Image Size (GB)2.7

Supporting Documentation and Metadata

Acquisition parameters for this Collection: Pre-operative post-biopsy MRI images of brain (DICOM format), segmentations (NIfTI format), and 1p-19q co-deletion data (text files).

 

Citations & Data Usage Policy 

This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

Please be sure to include the following citations in your work if you use this data set:

Data Citation

Authors. (2017). Data From LGG 1p19q Deletion. The Cancer Imaging Archive. http://doi.org

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. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper)

 

Other Publications Using This Data

  1.  https://arxiv.org/abs/1611.06939  Zeynettin Akkus, Issa Ali, Jiri Sedlar, Timothy L. Kline, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, Bradley J. Erickson. Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning. (2016).
  2. https://doi.org/10.1007/s10278-017-9965-6 Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick. Toolkits and Libraries for Deep Learning. Journal of Digital Imaging 2017 p1618-1627.


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

Version 1 (Current): Updated 2017/07/31

Data TypeDownload all or Query/Filter
Images (XX GB)
 
Segmentations (NiFTI)
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