• DocumentCode
    724895
  • Title

    Automatic segmentation of focal adhesions from mouse embryonic fibroblasts

  • Author

    Reyes-Aldasoro, Constantino Carlos ; Barri, Muruj ; Hafezparast, Majid

  • Author_Institution
    Biomed. Eng. Res. Centre, City Univ. London, London, UK
  • fYear
    2015
  • fDate
    16-19 April 2015
  • Firstpage
    548
  • Lastpage
    551
  • Abstract
    This work describes an automatic algorithm for the segmentation and quantification of focal adhesions from mouse embryonic fibroblasts. The main challenges solved by this algorithm are: the variability of the intensity of the focal adhesions, the detection of an outer ring, which distinguishes the cell periphery responsible for the cell migration, and the quantification of the characteristics of the focal adhesions. The algorithm detects maximal regions through gradients and uses a region-growing algorithm limited by intensity-based edges. The outer ring is calculated based on the average radial intensity from an extended centroid of the cell. Finally, traditional morphological characteristics are obtained to distinguish between two groups of cells. Two of the measurements employed showed statistical difference between two groups of cells.
  • Keywords
    adhesion; biomechanics; biomedical optical imaging; cell motility; edge detection; image segmentation; medical image processing; automatic focal adhesion segmentation; cell migration; intensity-based edges; morphological characteristics; mouse embryonic fibroblasts; region-growing algorithm; statistical analysis; Adhesives; Algorithm design and analysis; Fibroblasts; Image edge detection; Mice; Recruitment; Shape; MEF; cell segmentation; focal adhesions; mouse embryonic fibroblasts;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
  • Conference_Location
    New York, NY
  • Type

    conf

  • DOI
    10.1109/ISBI.2015.7163932
  • Filename
    7163932