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Localtab Group



Localtab
activetrue
titleData Access

Data Access

Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.

Data TypeDownload all or Query/Filter
Images and Segmentations (
DICOM,
2.7GB)
Image Removed
Image Removed
Segmentations only (
NIfTI, 2.9GB
DICOM)
(Redirects to large-file storage "Box"

(Download requires NBIA Data Retriever )

1p19q Status and Histologic Type



Click the Versions tab for more info about data releases.




Localtab
titleDetailed Description

Detailed Description


Collection Statistics

Updated 2020/06/26

Modalities

MRI, SEG, NIfTI

Number of Participants

159

Number of Studies

160

Number of Series

478

Number of Images

17519

Image Size (GB)2.7


Supporting Documentation and Metadata

For the 1p/19q status "n/n" means neither 1p nor 19q were deleted. "d/d" means 1p and 19q are co-deleted.





Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

Public collection license

Info
titleData Citation

Erickson, Bradley; Akkus, Zeynettin; Sedlar, Jiri; Korfiatis, Panagiotis. (2017). Data From LGG-1p19qDeletion. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/K9/TCIA.2017.dwehtz9v


Info
titlePublication Citation

Zeynettin Akkus, Issa Ali, Jiří Sedlář, Jay P. Agrawal, Ian F. Parney, Caterina Giannini, and Bradley J. Erickson.Predicting Deletion of Chromosomal Arms 1p/19q in Low-Grade Gliomas from MR Images Using Machine Intelligence. J Digit Imaging. 2017 Aug; 30(4): 469–476. Published online 2017 Jun 9.  DOI:  https://doi.org/10.1007/s10278-017-9984-3. PMCID: PMC5537096


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, Volume 26, Number 6 pp 1045-1057. DOI: https://doi.org/10.1007/s10278-013-9622-7

Other Publications Using This Data

  1. 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 that leverage our data. If you have a publication you'd like to add, please contact the TCIA Helpdesk.




Localtab
titleVersions

Version 2: Updated 6/26/2020

Data TypeDownload all or Query/Filter
Images and Segmentations (2.7GB)

 

(Download requires NBIA Data Retriever )

Segmentations only (DICOM)

(Download requires NBIA Data Retriever )

Segmentations (NIfTI, 2.9GB)

Image Removed

(Redirects to large-file storage "Box")

1p19q Status and Histologic Type

Previously the segmentations of the tumors were provided in NIfTI format and only included three axial slices (the one with the largest tumor diameter and ones below and above).   In version 2 segmentations of the entire T2 signal abnormality are provided in DICOM-SEG format.

Version 1 (Current): Updated 2017/09/30


Data TypeDownload all or Query/Filter
Images (2.7GB)

 
(Download requires NBIA Data Retriever )

Segmentations (NIfTI, 2.9GB)

(Redirects to large-file storage "Box")

1p19q Status and Histologic Type





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