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.
Principles, methods and state-of-the-art in auto-contouring
Relative performance of automatic and manual contouring, per method/solution and per organ-at-risk
Evaluation methods for automatic segmentation
This data set was provided to TCIA for use in the Challenge.
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Training Set Images (DICOM, 2.95 GB)
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Please be sure to include the following citations in your work if you use this data set:
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)
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