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A Knowledge-Anchored Integrative Image Search and Retrieval System

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Abstract

Clinical data that may be used in a secondary capacity to support research activities are regularly stored in three significantly different formats: (1) structured, codified data elements; (2) semi-structured or unstructured narrative text; and (3) multi-modal images. In this manuscript, we will describe the design of a computational system that is intended to support the ontology-anchored query and integration of such data types from multiple source systems. Additional features of the described system include (1) the use of Grid services-based electronic data interchange models to enable the use of our system in multi-site settings and (2) the use of a software framework intended to address both potential security and patient confidentiality concerns that arise when transmitting or otherwise manipulating potentially privileged personal health information. We will frame our discussion within the specific experimental context of the concept-oriented query and integration of correlated structured data, narrative text, and images for cancer research.

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Acknowledgments

Authors would like to thank Jason Buskirk, Felix Liu, Scott Silvey, Tremayne Smith, Ty Tolley and Herb Smaltz.

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Authors and Affiliations

  1. Information Warehouse, The Ohio State University Medical Center, 640 Ackerman Road, P.O. Box 183111, Columbus, OH, 43218, USA

    Selnur Erdal & Jyoti Kamal

  2. Department of Biomedical Informatics, The Ohio State University, Columbus, OH, 43210, USA

    Umit V. Catalyurek, Philip R. O. Payne, Joel Saltz & Metin N. Gurcan

Authors
  1. Selnur Erdal
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  2. Umit V. Catalyurek
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  3. Philip R. O. Payne
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  4. Joel Saltz
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  5. Jyoti Kamal
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  6. Metin N. Gurcan
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Correspondence to Selnur Erdal.

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Erdal, S., Catalyurek, U.V., Payne, P.R.O. et al. A Knowledge-Anchored Integrative Image Search and Retrieval System. J Digit Imaging 22, 166–182 (2009). https://doi.org/10.1007/s10278-007-9086-8

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  • DOI: https://doi.org/10.1007/s10278-007-9086-8

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