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Localtab Group


Localtab
activetrue
titleData Access

Data Access

C lick 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 and Radiation Therapy Structures (DICOM, 1.4 GB)

 

Deformation Vector Fields (MATLAB)

Click the Versions tab for more info about data releases.


Localtab
titleDetailed Description

Detailed Description

Collection Statistics


Modalities

CT, MR, RTSTRUCT, Matlab

Number of Participants

9

Number of Studies

25

Number of Series

61

Number of Images

3596

Image Size (GB)1.4

Supporting Documentation

Rachel B. Ger,Jinzhong Yang,Yao Ding,  Megan C. Jacobsen,  Carlos E. Cardenas,  Clifton D. Fuller,Rebecca M. Howell,  Heng Li,  R. Jason Stafford,  Shouhao Zhou,  Laurence E. Court. (2018) Synthetic head and neck and phantom images for determining deformable image registration accuracy in magnetic resonance imaging . Medical Physics. DOI: 10.1002/mp.13090


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

 This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

Please be sure to include the following citations in your work if you use this data set:

Public collection license
Info
titleData Citation

Rachel B. Ger, Jinzhong Yang, Yao Ding, Megan C. Jacobsen, Carlos E. Cardenas, Clifton D. Fuller, Rebecca M. Howell, Heng Li, R. Jason Stafford, Shouhao Zhou, Laurence E. Court (2018). Data from Synthetic and Phantom MR Images for Determining Deformable Image Registration Accuracy (MRI-DIR). The Cancer Imaging Archive. DOI: 10.7937/K9/TCIA.2018.3f08iejt


Info
titlePublication Citation

Rachel B. Ger,Jinzhong Yang,Yao Ding,  Megan C. Jacobsen,  Carlos E. Cardenas,  Clifton D. Fuller,Rebecca M. Howell,  Heng Li,  R. Jason Stafford,  Shouhao Zhou,  Laurence E. Court. (2018) Synthetic head and neck and phantom images for determining deformable image registration accuracy in magnetic resonance imaging. Medical Physics. DOI: 10.1002/mp.13090


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

TCIA maintains a list of publications which leverage our data. At this time we are not aware of any publications based on this data. If you have a publication you'd like to add please contact the TCIA Helpdesk.



Localtab
titleVersions

Version 1 (Current): Updated 2018/06/30

Data TypeDownload all or Query/Filter
Images (DICOM,  1.4 GB)

 

Deformation Vector Fields (MATLAB)




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