• DocumentCode
    2804906
  • Title

    Automatic detection of supraaortic branches and model-based segmentation of the aortic arch froM 3D CTA images

  • Author

    Biesdorf, A. ; Worz, Stefan ; von Tengg-Kobligk, H. ; Rohr, K.

  • Author_Institution
    Dept. Bioinf. & Functional Genomics, Univ. of Heidelberg, Heidelberg, Germany
  • fYear
    2009
  • fDate
    June 28 2009-July 1 2009
  • Firstpage
    486
  • Lastpage
    489
  • Abstract
    Automated quantification of the morphology of the aortic arch is crucial for diagnosis and treatment of cardiovascular diseases. We introduce a new approach for fully automatic segmentation and characterization of the aortic arch morphology for endovascular aortic repair. Supraaortic branches are detected based on an analysis of the connected components within a spherical volume around the vessel. Segmentation and quantification is based on a 3D parametric intensity model that is iteratively fitted to the image intensities and includes a fast and robust scheme for initialization. The performance of the approach has been evaluated using synthetic and real 3D CTA images.
  • Keywords
    angiocardiography; blood vessels; diagnostic radiography; image segmentation; medical image processing; 3D computed tomography angiography; 3D parametric intensity model; aortic arch morphology; automatic detection; endovascular aortic repair; fully automatic segmentation; supraaortic branches; Angiography; Bioinformatics; Biomedical imaging; Cancer; Cardiovascular diseases; Computer vision; Deformable models; Genomics; Image segmentation; Morphology; Aortic Arch Segmentation; Automatic Initialization; Branch Detection; Model-Based Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-3931-7
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2009.5193090
  • Filename
    5193090