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Driven by input from its scientific community, the Cancer Imaging Program (CIP) finds itself at the junction of two powerful scientific requisites; the need for cross-disciplinary research and inter-institutional data-sharing to speed scientific discovery and reduce redundancy, and the need to provide imaging phenotype data to augment large scale genomic analysis.

   

Image data collections on this archive offer an opportunity to encourage a new and emerging research community focused on connecting cancer phenotypes to genotypes by making available clinical images matched to the NIH TCGA (The Cancer Genome Atlas).  TCGA began in 2006 as a three-year pilot jointly sponsored by the National Cancer Institute and National Human Genome Research Institute. The TCGA pilot project (focused initially on glioblastoma, ovary, and lung cancers) confirmed that an atlas of genomic changes could be constructed for specific cancer types. It also showed that a national network of research and technology teams working on related projects could pool their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Importantly, it proved that making the data freely available would enable distributed researchers to make and validate important discoveries. The success of that pilot led the National Institutes of Health to commit major new resources to TCGA to collect and characterize more than 20 additional tumor types.

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