• DocumentCode
    2375857
  • Title

    Automatic delineation of the inner thoracic region in non-contrast CT data

  • Author

    Chittajallu, D.R. ; Balanca, P. ; Kakadiaris, I.A.

  • Author_Institution
    Depts. of Comput. Sci., Elec. & Comp. Eng., & Biomed. Eng., Univ. of Houston, Houston, TX, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    3569
  • Lastpage
    3572
  • Abstract
    The inner thoracic region consists of several important anatomical structures and an accurate delineation of this region is an essential step for various biomedical image analysis applications. In this paper, we present a fully automatic graph-based method for the delineation of the inner thoracic region in non-contrast cardiac CT data. In particular, we reformulate the problem of delineating the inner thoracic region as an optimal surface segmentation problem, the solution to which is obtained by computing the minimum-cost closed set in a node-weighted directed graph. Comparing the results obtained using our method with manual segmentations performed by an expert on non-contrast cardiac CT scans of 20 randomly selected patients indicated an overlap of 99.1 plusmn 0.2%.
  • Keywords
    computerised tomography; directed graphs; image segmentation; medical image processing; anatomical structure; automatic delineation; biomedical image analysis; inner thoracic region; minimum-cost closed set; node weighted directed graph; noncontrast CT data; surface segmentation problem; Algorithms; Artificial Intelligence; Automation; Computer Simulation; Heart; Humans; Imaging, Three-Dimensional; Lung; Models, Statistical; Pattern Recognition, Automated; Radiographic Image Interpretation, Computer-Assisted; Radiography, Thoracic; Reproducibility of Results; Tomography, X-Ray Computed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5332585
  • Filename
    5332585