• DocumentCode
    1553449
  • Title

    Information fusion, application to data and model fusion for ultrasound image segmentation

  • Author

    Solaiman, B. ; Debon, R. ; Pipelier, F. ; Cauvin, J.M. ; Roux, C.

  • Author_Institution
    ENST de Bretagne, Brest, France
  • Volume
    46
  • Issue
    10
  • fYear
    1999
  • Firstpage
    1171
  • Lastpage
    1175
  • Abstract
    Nowadays, information fusion constitutes a challenging research topic. The authors´ study proposes to achieve the fusion of several knowledge sources. This, in order to detect the esophagus inner wall from ultrasound medical images. After a brief description of information fusion concepts, the authors propose a system architecture including both model and data fusion. The data fusion is accomplished using fuzzy modeling, which can be seen as a monosensor/multiple sources data fusion system. The model fusion is performed using a full-adapted snake theory, which projects the fuzzy decision into the binary decision space.
  • Keywords
    biological organs; biomedical ultrasonics; edge detection; fuzzy set theory; image segmentation; medical image processing; modelling; sensor fusion; binary decision space; esophagus inner wall detection; full-adapted snake theory; fuzzy decision; knowledge sources; medical diagnostic imaging; system architecture; ultrasound medical images; Biomedical imaging; Decision making; Esophagus; Fuzzy logic; Fuzzy systems; Humans; Image segmentation; Sensor fusion; Sensor systems; Ultrasonic imaging; Computer Simulation; Endoscopes; Endosonography; Equipment Design; Esophageal Neoplasms; Esophagus; Fuzzy Logic; Humans; Image Enhancement; Transducers;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.790491
  • Filename
    790491