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Rules for data usage

The SKI10 challenge is organized in the spirit of cooperative scientific progress. We therefore ask anybody using this website to respect the rules below.

  • The original data sets and associated segmentation data downloaded here, or any data derived from these data sets, must not be given nor redistributed under any circumstances to persons not belonging to the registered team.
  • The provided data is to be used exclusively for the purpose of developing segmentation algorithms for the knee and evaluating them via this website. Use of the data for any other purposes requires explicit permission from Bryan Morrison.
  • Commercial use of segmentation algorithms that use the provided data (test or training cases) as training material is not allowed.
  • Submitted segmentation results will be made publicly available on this website, and by submitting results, you grant us permission to do so. Obviously, teams maintain full ownership and rights to their methods and algorithms.

  • If results of algorithms in this challenge are to be used in scientific publications (journal publications, conference papers, technical reports, presentations at conferences and meetings) you must always report the official results from this website. You are not allowed to publish results evaluated by yourself on the provided training data.
    In addition, you must cite the following paper:

    T. Heimann, B.J. Morrison, M.A. Styner, M. Niethammer, S.K. Warfield: Segmentation of Knee Images: A Grand Challenge. In: Proc. MICCAI Workshop on Medical Image Analysis for the Clinic, pp. 207-214, 2010.

    This paper is available here.  - Each submitted result must be accompanied by a pdf file describing the workings of the system. The maintainers of this site reserve the right to refuse to evaluate systems whose description does not meet minimal requirements. See here for more explanation about the required description. - The maintainers of this site may use the submitted results for future research studies, for example by investigating methods that combine results from multiple systems. If your results will be used, your work will be referenced.