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All of these imaging disciplines have created mutually-exclusive yet rich essential data sets. The barriers between them, which are created by proprietary data formats and a lack of common shared standards, mean that the promise of integrating them awaits a technical solutions, . A significant start to these technical solutions that comprise the National Cancer Institute Clinical and Translational Imaging Informatics Project (NCI CTIIP) and its sub-projects.

CTIIP Sub-Projects

It is now feasible to extract large sets of quantitative image features relevant to cancer prognosis or treatment across three complementary research domains: clinical imaging, pre-clinical imaging, and digital pathology. These high-dimensional image feature sets can be used to infer clinical phenotypes or correlate with gene–protein signatures. This type of analysis, however, requires large volumes of data.

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