• DocumentCode
    3512594
  • Title

    Improved 3D automatic segmentation and measurement of pleural effusions

  • Author

    Bliton, John ; Yao, Jianhua ; Bi, Mark ; Summers, Ronald M.

  • Author_Institution
    Radiol. & Image Sci. Dept., Nat. Institutes of Health, Bethesda, MD, USA
  • fYear
    2011
  • fDate
    March 30 2011-April 2 2011
  • Firstpage
    1954
  • Lastpage
    1957
  • Abstract
    Pleural effusions are accumulations of fluid in the pleural space, usually associated with atelectasis of the adjacent lung. We have previously presented an automated method to measure the volume of pleural effusions on chest CT images. This paper presents an improved version of the same method, which adds 3D surface modeling and additional propagation of the segmentation in the inferior direction. The improved method is also more robust to noise. We compared this method to manual segmentations and the previous method by applying it to 15 chest CT scans. The new segmentation, on average, increased estimated effusion volume by 11%, bringing it closer to the expected average. In addition, the correlation between manual and automatic effusion volumes increased from .59 to .81 (p = .13), indicating a better segmentation.
  • Keywords
    biological fluid dynamics; computerised tomography; diseases; image segmentation; lung; medical image processing; 3D automatic segmentation; 3D surface modeling; atelectasis; chest CT images; effusion volume; lung; pleural effusions; Computed tomography; Image segmentation; Lungs; Manuals; Pixel; Surface morphology; Three dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
  • Conference_Location
    Chicago, IL
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-4127-3
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2011.5872792
  • Filename
    5872792