• DocumentCode
    2652716
  • Title

    Incorporating variance within binary flow for leukocyte tracking

  • Author

    Janiczek, Rob L. ; Tang, Jinshan ; Acton, Scott T.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Virginia Univ., Charlottesville, VA, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    7-10 Nov. 2004
  • Firstpage
    1838
  • Abstract
    Tracking leukocytes in vivo is vital in determination of the roles and significance of integrins and selectins within the inflammation process and the effectiveness of anti-inflammatory drugs. In this paper, we propose a region-based snake for segmenting objects in the presence of inhomogeneities. We then use this geometric snake to track leukocytes in intravital microscopy. The results show that the binary flow algorithm introduced here improves upon the traditional binary flow algorithm and the gradient vector flow algorithm both in terms of percentage of frames tracked and the root mean squared error.
  • Keywords
    blood; cellular biophysics; image reconstruction; image segmentation; mean square error methods; medical image processing; microscopy; statistics; tracking; antiinflammatory drugs; binary flow; geometric snake; gradient vector flow algorithm; inflammation process; intravital microscopy; leukocyte tracking; object segmentation; root mean squared error; Active contours; Drugs; Image reconstruction; Image segmentation; In vivo; Microscopy; Noise reduction; Shape; Statistics; White blood cells;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
  • Print_ISBN
    0-7803-8622-1
  • Type

    conf

  • DOI
    10.1109/ACSSC.2004.1399482
  • Filename
    1399482