The Cancer Imaging Archive (TCIA) Public Access

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Localtab Group


Localtab
activetrue
titleData Access

Data Access

Data TypeDownload all or Query/Filter

Images (DICOM, XX.X GB)


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(Download requires the NBIA Data Retriever)

Images (Niftinifti, zip, XX.156 GB)

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Clinical data (CSV)
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UCSF-

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Genomics (csv)

PDGM-metadata.csv

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Click the Versions tab for more info about data releases.

Please contact help@cancerimagingarchive.net  with any questions regarding usage.


Localtab
titleDetailed Description

Detailed Description

Image Statistics


Modalities

MR

Number of Patients

500

Number of Studies


Number of Series


Number of Images


Images Size (GB)
<< Add any additional information as needed below. Likely would be something from site. >>


All image data have been "skull stripped", deidentified, pre-processed per the methods section of our abstract, and converted to NIfTI format. We cannot provide original DICOM data, however, these pre-processed files have been prepared to facilitate the type of research that this dataset is intended for.


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

Tcia license 4 international

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titleData Citation

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


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titlePublication Citation

We ask on the proposal form if they have ONE traditional publication they'd like users to cite.


Info
titleAcknowledgement
  • Research was supported by the National Institutes of Health Ruth L. Kirschstein Institutional National Research Service Award under award number T32EB001631 and
  • by the RSNA Research & Education Foundation under grant number RR2011. The content is solely the responsibility of the authors and does not necessarily represent the official views of the RSNA R&E Foundation.


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. 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. DOI: 10.1007/s10278-013-9622-7

Other Publications Using This Data

  • Calabrese E, Rudie JD, Rauschecker AM, Villanueva-Meyer JE, Cha S. Feasibility of Simulated Postcontrast MRI of Glioblastomas and Lower Grade Gliomas Using 3D Fully Convolutional Neural Networks. Radiology: Artificial Intelligence. 2021 May 19;e200276.

  • Calabrese E, Villanueva-Meyer JE, Cha S. A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas. Scientific Reports. 2020 Jul 16;10(1):11852.

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.


Localtab
titleVersions

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

Data TypeDownload all or Query/Filter
Images (DICOM, xx.x GB)


Tcia button generator



Tcia button generator
labelSearch



(Requires NBIA Data Retriever.)

Clinical Data (CSV)Link
Other (format)


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labelSearch



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