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  • Lung CT Segmentation Challenge 2017 (LCTSC)

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Summary

Excerpt

The overall objective of this auto-segmentation grand challenge is to provide a platform for comparison of various auto-segmentation algorithms when they are used to delineate four organs at risk (OARs) from CT images for patients in radiation treatment planning with the same cancer or different types, sizes and locations in chest. The results will provide an indication of the performances achieved by various auto-segmentation algorithms and can be used to guide the selection of these algorithms for clinic use if desirable.

Learning objectives:

  1. Principles, methods and state-of-the-art in auto-contouring
  2. Relative performance of automatic and manual contouring, per method/solution and per organ-at-risk
  3. Evaluation methods for automatic segmentation

This data set was provided to TCIA for use in he Challenge.

 

Localtab Group
Localtab
activetrue
titleData Access

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.

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Images (DICOM, XXX MB) 

Click the Versions tab for more info about data releases.

Localtab
titleDetailed Description

Detailed Description

Collection Statistics

Updated 2017/05/17

Modalities 

CT, RT

Number of Patients

 

Number of Studies

 

Number of Series

 

Number of Images

 

Image Size (MB) 

Supporting Documentation and Metadata

Supporting documentation is available for this collection???

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:

Info
titleData Citation

 (2017). Data From XXXX The Cancer Imaging Archive. http://doi.org

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 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 2017/05/17

Data TypeDownload all or Query/Filter
Images (XXX MB)