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Digital Pathology and Integrated Query System

Digital Pathology

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 component of this sub-project proposes to leverage several open source 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, 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. 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 Data federation, a process whereby data is collected from different databases without ever copying or transferring the original data, is part of the solution as well. It requires a shared semantic scheme and a supporting software framework to link the databases. The software used to accomplish data federation in this sub-project is Bindaas. Bindaas is middleware that is also used to build the backend infrastructure of caMicroscope. We propose to extend this backend infrastructure The team is extending Bindaas with a data federation capability that provides for query capability using multiple data points across makes it possible to query data from TCIA and TCGA will be implemented.

Integrating Imaging and Molecular Data

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