• DocumentCode
    1620474
  • Title

    Fast Automatic Segmentation of Nuclei in Microscopy Images of Tissue Sections

  • Author

    Laurain, V. ; Ramoser, H. ; Nowak, C. ; Steiner, G.E. ; Ecker, R.

  • Author_Institution
    Advanced Comput. Vision GmbH, Vienna
  • fYear
    2006
  • Firstpage
    3367
  • Lastpage
    3370
  • Abstract
    In this paper, we present a segmentation method for nuclei in microscopy images of tissue sections. The proposed method is completely automatic and performs well in the conflicting aims of speed efficiency, detection accuracy and shape fitting. It proposes an efficient alternative to existing methods, in achieving the three main usual segmentation steps: (i) background extraction, (ii) seed finding and (iii) seed growing. Eventually, some significant results are depicted and discussed
  • Keywords
    biological tissues; biomedical optical imaging; image segmentation; medical image processing; optical microscopy; background extraction; detection accuracy; fast automatic segmentation; microscopy images; nuclei; seed finding; seed growing; shape fitting; speed efficiency; tissue sections; Clustering algorithms; Computer vision; Data mining; Fluorescence; Histograms; Image segmentation; Microscopy; Pixel; Robustness; Working environment noise; Nuclei; microscopy images; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1617199
  • Filename
    1617199