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The goal of this foundational sub-project is to create a digital pathology image server that can accept images from multiple domains and run integrative queries on that data. Using this server, which is an extended version of caMicroscope, researchers can select data from different imaging data sets and use them in image algorithms. The first data sets that are being integrated on this image server , which is an extended version of caMicroscope, are TCGA and TCIA.

The TCGA project is producing a comprehensive genomic characterization and analysis of 200 types of cancer and providing this information to the research community. TCIA and the underlying National Biomedical Image Archive (NBIA) manage well-curated, publicly-available collections of medical image data. The linkages between TCGA and TCIA are valuable to researchers who want to study diagnostic images associated with the tissue samples sequenced by TCGA.

Although TCGA and TCIA comprise a rich, complementary, multi-discipline data set, they are in an infrastructure that provides limited ability to query the data. Researchers want to query both databases together at the same time to identify cases based on all available data types. Moreover, without common data standards, it's impossible to integrate While TCGA and TCIA data with data sets from the less complementary are DICOM-compliant, digital pathology and co-clinical/small animal model environments do not share the same data standards or do not use them consistently.

To address these limitations, the CTIIP team is developing a unified query interface to make it easier to analyze data from different research disciplines represented by TCGA, TCIA, and co-clinical/small animal model data. It model data. The lack of common data standards will not be a hindrance to data analysis, since the server that the unified query interface is on will accept whole slides without recoding. The unified query interface will also provide a common platform and data engine for the hosting of “pilot challenges.” These pilot ," which are described in more detail below. Pilot challenges will advance biological and clinical research in a way that also integrates the clinical, co-clinical/small animal model, and digital pathology imaging disciplines.

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The purpose of the digital pathology component of CTIIP is to support data mashups between image-derived information from TCIA and clinical and molecular metadata from TCGA. The team is using OpenSlide, a vendor-neutral C library, to extend the software of caMicroscope, a digital pathology server, to provide the infrastructure for these data mashups. The extended software will support some of the common formats adopted by whole slide vendors as well as basic image analysis algorithms. With the incorporation of common whole slide formats, caMicroscope will be able to read whole slides without recoding, which often introduces additional compression artifacts. With the addition of support for basic image analysis algorithms, (CKK: what?the following things can happen...). These additional features of caMicroscope will make it possible to conceptually integrate digital pathology images within TCIA and NBIA and provide a logical bridge from proprietary pathology formats to DICOM standards.

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We are pulling data out of caDSR (ER negative and positive, other common data elements) and we are asking Bob Cardiff's team to ask the same questions so that we can compare human and mouse data. 

If you did an integrative query, how would you do it? Data calls to do different integrative queries. How would you use sufficient standard data. Come out with information that will allow you to make a decision. Pilot challenges to compare the decision support systems for three domains.

We need a clear explanation of how to do this.

Explain our complicated project in a simple manner so they understand why we are doing and what we are doing.

Pathology problems:1.  proprietary data formats that cannot be displayed and manipulated in the same tools. Solution is to integrate caMicroscope with OpenSlide (allows us to read prop. formats without converting images). Makes a large number of image formats accessible. 2. no standard for markups and annotations. So we're creating microAIM.

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