• DocumentCode
    406584
  • Title

    Velocity-aided cardiac segmentation

  • Author

    Cho, Jinsoo ; Brummer, Marijn ; Benkeser, Paul J.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    17-21 Sept. 2003
  • Firstpage
    622
  • Abstract
    Segmentation of myocardial boundaries, especially the endocardial boundary, in images from magnetic resonance imaging (MRI) often suffers from flow-related signal loss, partial volume effects, and the presence of papillary muscles. To address these problems, a velocity-aided cardiac segmentation method based a modified active contour model with the orientation gradient force has been developed. Unlike other MRI cardiac segmentation methods based on active contour models, the velocity images from phase contrast MRI, together with the magnitude images, were used to derive an additional external force from the orientation gradient. The velocity images were also used to track the initial seed contours throughout the entire cardiac cycle to reduce the propagation of errors in sequential segmentation. The linear correlation coefficients and boundary matching descriptors of segmented boundaries were calculated relative to manually segmented reference boundaries to assess the accuracy of this method. Results of segmentation of the endocardial boundaries were encouraging in both individual frame segmentation and sequential frame segmentation.
  • Keywords
    biomedical MRI; cardiology; image segmentation; image sequences; medical image processing; MRI; MRI cardiac segmentation methods; active contour model; boundary matching descriptors; cardiac cycle; endocardial! boundary; flow-related signal loss; individual frame segmentation; linear correlation coefficients; magnetic resonance imaging; myocardial boundaries segmentation; orientation gradient force; papillary muscles; partial volume effects; phase contrast MRI; segmented boundaries; sequential frame segmentation; sequential segmentation; velocity images; velocity-aided cardiac segmentation; Active contours; Biomedical computing; Biomedical engineering; Cardiac disease; Image edge detection; Image segmentation; Magnetic resonance imaging; Muscles; Myocardium; Radiology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-7789-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2003.1279830
  • Filename
    1279830