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  • Crowds Cure Cancer: Data collected at the RSNA 2018 annual meeting

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For RSNA 2018, the application was re-designed to promote more comprehensive data collection and increased community participation. Participants were instructed to identify all metastatic disease and provide details regarding image quality, lesion location and characteristics. To provide additional incentives for participation, we improved the system by adding gamification features (e.g., reward badges), and created a leaderboard to display participant standings.  The amount of data being annotated was also significantly increased to include CT scans from 324 patients spanning 13 TCIA collections: Anti-PD-1_LungAnti-PD-1_MELANOMACPTAC-CCRCCCPTAC-GBMCPTAC-HNSCCCPTAC-PDACPTAC-UCECNSCLC RadiogenomicsTCGA-BLCATCGA-COADTCGA-HNSCTCGA-LUSCTCGA-UCEC.  During RSNA 2018, 4756 bi-directional measurements were obtained compared to 2345 uni-dimensional measurements in 2017. Of the 4756 measurements, 65% of the lesions were annotated with location information. The data is being released in DICOM Structured Report and CSV formats for analysis by the community. The application is available on GitHub https://github.com/crowds-cure/cancer.


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

Data TypeDownload all or Query/Filter
Images annotated by participants (DICOM)

Crowd measurements (CSV)

Structured reports (DICOM-SR)

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


Localtab
titleDetailed Description

Detailed Description

Data resulting from this experiment is available in the following formats:

  • Source DICOM scans annotated by participants
  • CSV representation of crowd measurements
  • DICOM-SR representation of crowd measurements


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

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

Trinity Urban, Erik Ziegler, Steve Pieper, Justin Kirby, Daniel Rukas, Britney Beardmore, Bhanusupriya Somarouthu, Evren Ozkan, Gustavo Lelis, Brenda Fevrier-Sullivan, Samarth Nandekar, Andrew Beers, Carl Jaffe, John Freymann, David Clunie, Gordon J. Harris, Jayashree Kalpathy-Cramer. Crowds Cure Cancer: Data collected at the RSNA 2018 annual meeting. The Cancer Imaging Archive. doi: 10.7937/TCIA.2019.yk0gm1eb


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. (paper)

Other Publications Using This Data

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


Localtab
titleVersions

Version 1 (Current): 2019/05/30

Data TypeDownload all or Query/Filter
Images annotated by participants (DICOM)

Crowd measurements (CSV)

Structured reports (DICOM-SR)



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