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Summary

Acknowledgements

  • Site to provide acknowledgements including grant information.

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.

Data TypeDownload all or Query/Filter

Images, Segmentations, and Radiation Therapy Structures (DICOM, XX.X GB)

 

Download and Search buttons not operatonal until data released.

Click the Versions tab for more info about data releases.

Detailed Description

Image Statistics


Modalities

MR, RTSTRUCT, RTDOSE, RTPLAN

Number of Participants

242

Number of Studies

242

Number of Series

1936

Number of Images

48582

Images Size (GB)

Citations & Data Usage Policy

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 4.0 International License under which it has been published. Attribution should include references to the following citations:


Data Citation

Shapey, J., Kujawa, A., Dorent, R., Wang, G., Bisdas, S., Dimitriadis, A., Grishchuck, D., Paddick, I., Kitchen, N., Bradford, R., Saeed, S., Ourselin, S., Vercauteren, T. (2020). Segmentation of vestibular schwannoma from magnetic resonance imaging: An open annotated dataset and baseline algorithm (Vestibular-Schwannoma-SEG) [Data Set]. The Cancer Imaging Archive. DOI Pending.​

Publication Citation

Shapey, J., Wang, G., Dorent, R., Dimitriadis, A., Li, W., Paddick, I., Kitchen, N., Bisdas, S., Saeed, S. R., Ourselin, S., Bradford, R., and Vercauteren, T. (2019). An artificial intelligence framework for automatic segmentation and volumetry of vestibular schwannomas from contrast-enhanced T1-weighted and high-resolution T2-weighted MRI. Journal of Neurosurgery JNS , 1-9, available from: < https://doi.org/10.3171/2019.9.JNS191949>

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. DOI: https://doi.org/10.1007/s10278-013-9622-7

Acknowledgement

This work was supported by Wellcome Trust (203145Z/16/Z, 203148/Z/16/Z, WT106882) and EPSRC (NS/A000050/1, NS/A000049/1) funding. Tom Vercauteren is also supported by a Medtronic/Royal Academy of Engineering Research Chair (RCSRF1819\7\34).

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.

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

Data TypeDownload all or Query/Filter
Images, Segmentations, and Radiation Therapy Structures (DICOM, xx.x GB)

(Requires NBIA Data Retriever .)






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