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Bridging the Text-Image Gap: a Decision Support Tool for Real-Time PACS Browsing.

In this paper, we introduce an ontology-based technology that bridges the gap between MR images on the one hand and knowledge sources on the other hand. The proposed technology allows the user to express interest in a body region by selecting this region on the MR image he or she is viewing with a m...

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Published in:Journal of Digital Imaging Vol. 25; no. 2; pp. 227 - 240
Main Authors: Sevenster, Merlijn, Ommering, Rob, Qian, Yuechen
Format: diagnostic images research tables/charts Journal Article
Published: Springer Nature Apr2012
Online Access:View this record in EBSCOhost
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      dt: Apr2012
      vid: 25
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      pub: Springer Nature
      place: New York, New York
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        atl: Bridging the Text-Image Gap: a Decision Support Tool for Real-Time PACS Browsing.
      aug:
        au:
          Sevenster, Merlijn
          Ommering, Rob
          Qian, Yuechen
        affil: Philips Research Europe, Prof. Holstlaan 4 5656AA Eindhoven the Netherlands
      sug:
        subj:
          Picture Archiving and Communication Systems
          Magnetic Resonance Imaging
          Reference Tools
          Information Retrieval
          Decision Support Techniques
          Human
          Algorithms
          Systems Design
          Semantics
          Pilot Studies
          Evaluation Research
          Snomed
          Natural Language Processing
          Artificial Intelligence
      ab: In this paper, we introduce an ontology-based technology that bridges the gap between MR images on the one hand and knowledge sources on the other hand. The proposed technology allows the user to express interest in a body region by selecting this region on the MR image he or she is viewing with a mouse device. The proposed technology infers the intended body structure from the manual selection and searches the external knowledge source for pertinent information. This technology can be used to bridge the gap between image data in the clinical workflow and (external) knowledge sources that help to assess the case with increased certainty, accuracy, and efficiency. We evaluate an instance of the proposed technology in the neurodomain by means of a user study in which three neuroradiologists participated. The user study shows that the technology has high recall (>95%) when it comes to inferring the intended brain region from the participant's manual selection. We are confident that this helps to increase the experience of browsing external knowledge sources.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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