• DocumentCode
    1594076
  • Title

    Extension of Deformable Models: Hybrid Approaches for Analysis of Medical Images

  • Author

    Ourselin, Sébastien ; Li, Rongxin

  • Author_Institution
    Autonomous Syst. Lab., CSIRO ICT Centre, Sydney, NSW
  • fYear
    2005
  • fDate
    6/27/1905 12:00:00 AM
  • Firstpage
    7182
  • Lastpage
    7185
  • Abstract
    Despite deformable models´ wide applicability in medical image segmentation, they are sometimes not adequate by themselves to achieve a desired degree of automation, a guaranteed level of accuracy, or an outcome beyond segmentation. In such situations, other methods may be combined with a deformable model to extend its abilities, overcome its shortcomings or increase the assurance of the segmentation accuracy. As examples of such combinations, we discuss the use of deformable models in hybrid approaches, to obtain curvilinear models of tubular structures, patient specific models of the abdominal aortic vessel system, and tissue models for radiation simulation
  • Keywords
    biomedical MRI; blood vessels; computerised tomography; image segmentation; medical image processing; CT images; MRI; abdominal aortic vessel system; deformable models; medical image segmentation; patient specific models; radiation simulation; tissue models; tubular structures; Abdomen; Automation; Biomedical imaging; Biomedical measurements; Computed tomography; Deformable models; Image analysis; Image segmentation; Pathology; Power system modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1616165
  • Filename
    1616165