• DocumentCode
    2357614
  • Title

    Ontology-based medical image annotation with description logics

  • Author

    Hu, Bo ; Dasmahapatra, Srinandan ; Lewis, Paul ; Shadbolt, Nigel

  • Author_Institution
    Dept. of Electron. & Comput. Sci., Southampton Univ., UK
  • fYear
    2003
  • fDate
    3-5 Nov. 2003
  • Firstpage
    77
  • Lastpage
    82
  • Abstract
    The interpretation of medical evidence is normally presented in terms of a controlled, but diversely expressed specialist vocabulary and natural language phrases. Such informally expressed data require human intervention to ascertain its relevance in any specific case. In order to facilitate machine-based reasoning about the evidence gathered, additional interpretive semantics must be attached to the data; a shift from a merely data-intensive approach to a semantics-rich model of evidence. In this paper, we present a system to formally annotate medical images captured to aid the diagnosis and management of breast cancer, that enables a series of semantics-based operations to be performed. Our approach is grounded upon an imaging ontology specifying the domain knowledge and a description logic (DL) taxonomic inferential engine responsible for semantics-based reasoning and image retrieval.
  • Keywords
    image retrieval; inference mechanisms; medical diagnostic computing; medical image processing; medical information systems; breast cancer diagnosis; breast cancer management; data-intensive approach; description logics; image retrieval; imaging ontology; interpretative semantics; machine-based reasoning; medical evidence interpretation; natural language phrases; ontology-based medical image annotation; semantics-based image; semantics-based operation; semantics-based reasoning; semantics-rich model; specialist vocabulary; Biomedical imaging; Breast cancer; Engines; Humans; Image retrieval; Logic; Medical diagnostic imaging; Natural languages; Ontologies; Vocabulary;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    0-7695-2038-3
  • Type

    conf

  • DOI
    10.1109/TAI.2003.1250173
  • Filename
    1250173