• DocumentCode
    2364231
  • Title

    Automated model driven localization of the heart and lung surfaces in thoracic MR images

  • Author

    Lelieveldt, BPF ; Van der Geest, JR ; Reiber, JHC

  • Author_Institution
    Div. of Image Process., Leiden Univ. Med. Center, Netherlands
  • fYear
    1998
  • fDate
    13-16 Sep 1998
  • Firstpage
    9
  • Lastpage
    12
  • Abstract
    Proposes a representation for anatomical shape knowledge, by which the boundaries of the heart and lungs can be localized automatically in thoracic MR sets. The major organs in the thorax are described in a compact mathematical model by combining a set of fuzzy implicit surfaces by means of Constructive Solid Geometry (CSG). The resulting shape description captures both the single organ shape and their spatial context in a boundary potential function. This model potential allows an automated model-image matching step, in which the model is fitted to an image set of a different subject. The matching method was tested on 15 clinical thoracic MR scans front 13 different subjects. In 13 cases, the lung and heart surfaces were localized within a margin of 10 mm. The matching method is applicable to thoracic MR data irrespective of ifs planar orientation, provided that a major parr of the thorax is present in the image volume
  • Keywords
    biomedical MRI; cardiology; edge detection; image matching; lung; medical image processing; physiological models; 10 mm; anatomical shape knowledge representation; automated model driven localization; automated model-image matching step; boundary potential function; constructive solid geometry; fuzzy implicit surfaces; heart surfaces; lung surfaces; magnetic resonance imaging; medical diagnostic imaging; single organ shape; thoracic MR images; Context modeling; Fuzzy sets; Geometry; Heart; Image segmentation; Layout; Lungs; Shape; Solid modeling; Thorax;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers in Cardiology 1998
  • Conference_Location
    Cleveland, OH
  • ISSN
    0276-6547
  • Print_ISBN
    0-7803-5200-9
  • Type

    conf

  • DOI
    10.1109/CIC.1998.731696
  • Filename
    731696