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As explained in the Challenge Management System Evaluation Report, challenge hosts and participants cannot do it alone. The computing resourcing needed to process these large datasets may be beyond what is available to individual participants. For the organizers, creating an infrastructure that is secure, robust, and scalable can require resources that are beyond the reach of many researchers. Additionally, imaging formats for pathology images can be proprietary and interoperability between formats can require additional software development efforts.

Over the last few years, “Grand Challenges” Grand Challenges

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have become popular in several imaging-based research communities. A Grand Challenge is designed to validate and compare imaging analysis algorithms. The algorithms are applied to a single dataset and the results for each algorithm are compared against a previously-determined ground-truth dataset.

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