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A knowledge-anchored integrative image search and retrieval system.

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 des...

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Published in:Journal of Digital Imaging Vol. 22; no. 2; pp. 166 - 183
Main Authors: Erdal S, Catalyurek UV, Payne PRO, Saltz J, Kamal J, Gurcan MN
Format: pictorial tables/charts Journal Article
Published: Springer Nature Apr2009
Online Access:View this record in EBSCOhost
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      dt: Apr2009
      vid: 22
      iid: 2
      pid: 237
      pub: Springer Nature
      place: New York, New York
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        105483054
        2010229050
        10.1007/s10278-007-9086-8
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        atl: A knowledge-anchored integrative image search and retrieval system.
      aug:
        au:
          Erdal S
          Catalyurek UV
          Payne PRO
          Saltz J
          Kamal J
          Gurcan MN
        affil: Information Warehouse, The Ohio State University Medical Center, 640 Ackerman Road, P.O. Box 183111, Columbus, OH 43218, USA. selnur.erdal@osumc.edu
      sug:
        subj:
          Computers and Computerization
          Image Retrieval Systems
          Image Retrieval Methods
          Information Systems Methods
          Classification
          Electronic Health Records
          Data Warehouse
          DICOM
          Health Information Systems
          Information Needs
          Patient Record Systems
          Picture Archiving and Communication Systems
          Systems Design
          Systems Integration
          Unified Medical Language System
          Vocabulary, Controlled
      ab: 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.
      pubtype: Academic Journal
      doctype:
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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