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Digital pathology, unlike its more mature radiographic counterpart, has yet to standardize on a single storage and transport media. In addition, each pathology-imaging vendor produces its own image management systems, making image analysis systems proprietary and not standardized. The result is that images produced on different systems cannot be analyzed via the same mechanisms. Not only does this lack of standards and the dominance of proprietary formats impact digital pathology, but it prevents digital pathology data from integrating with radiographic, genomic, and proteomic data.

This project proposes to leverage several open source and previously NCI-funded activities to provide an open source digital pathology image server that can host and serve digital pathology images for any of the major vendors without recoding, which often introduces additional compression artifacts. A single digital pathology server would allow NCI to include digital pathology images within TCIA / NBIA and provide a logical bridge from proprietary pathology formats to DICOM standards. Specifically, we are proposing to the team will expand the functionality of the caMicroscope digital pathology platform to include support for some of the common formats adopted by whole slide vendors. This functionality would be made possible by use of the Openslide library. If time and funds allow, we would also expand the OpenSlide library to include the Olympus file format (the only format not currently supported)The Openslide library would make this functionality possible.

The recently concluded FDA Imaging Pilot demonstrated the feasibility of data federation between NBIA and AIM, and the value of such data federation in streamlining the imaging review processes at the FDA. This data federation is made possible by the Bindaas middleware that is also used to build the backend infrastructure of caMicroscope. We propose to extend this backend infrastructure with a data federation capability that provides for query capability using multiple data points across TCIA and TCGA will be implemented.

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