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Summary


Excerpt

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Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • Stanford University School of Medicine, Stanford, California, USA - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.
    A complete list of acknowledgements can be found here.

Localtab Group


Localtab
activetrue
titleData Access

Data Access

Click the Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.

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Images (DICOM, XX.X GB)

 

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Images (NIfTI, zip)

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The download and search buttons will not work for DICOM images until the collection has completed curation.

Click the Versions tab for more info about data releases.


Localtab
titleDetailed Description

Detailed Description

Image Statistics


Modalities

CT, SEG

Number of Patients

32

Number of Studies

32

Number of Series

64

Number of Images

9632

Images Size (GB)

Images size will be added when curation is complete

(Add any additional information as needed here)


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

Add any special restrictions in here.

These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:

Info
titleData Citation

 Jaggi, A.,  Mattonen, S. A. ,  McNitt-Gray, M., & Napel, S. (2020). Data from the Stanford DRO Toolkit: Digital Reference Objects for Standrdization of Radiomic Features [Data set]. The Cancer Imaging Archive. https://doi.org/(DOI goes here).


Info
titlePublication Citation

Jaggi, A., Mattonen, S., McNitt-Gray, M., Napel, S (2020). Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features. Accepted for publication pending minor revisions, Tomography, Feb. 2020


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


Info
titleGrant Citations
  • David Geffen School of Medicine at UCLA - U01CA181156
  • Stanford University School of Medicine – U01CA187947 and U24CA180927
  • University of Michigan - U01CA232931
  • University of Washington – R50CA211270, U01CA148131
  • University of South Florida - U24CA180927, U01CA200464
  • Moffitt Cancer Center – U01CA143062, U01CA200464, P30CA076292
  • UC San Francisco - U01CA225427
  • BC Cancer Research Centre - NSERC Discovery Grant: RGPIN-2019-06467
  • Columbia University- U01CA225431
  • Center for Biomedical Image Computing and Analytics at the University of Pennsylvania - U24CA189523, R01NS042645
  • Massachusetts General Hospital- U01CA154601, U24CA180927


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.


Localtab
titleVersions

Version 1 (Current): Updated yyyy/mm/dd

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

(Requires NBIA Data Retriever.)

Images (NIfTI, zip)

Supplemental (json, zip)