• DocumentCode
    1754421
  • Title

    An Efficient Technique for Nuclei Segmentation Based on Ellipse Descriptor Analysis and Improved Seed Detection Algorithm

  • Author

    Hongming Xu ; Cheng Lu ; Mandal, Mrinal

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Alberta, Edmonton, AB, Canada
  • Volume
    18
  • Issue
    5
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    1729
  • Lastpage
    1741
  • Abstract
    In this paper, we propose an efficient method for segmenting cell nuclei in the skin histopathological images. The proposed technique consists of four modules. First, it separates the nuclei regions from the background with an adaptive threshold technique. Next, an elliptical descriptor is used to detect the isolated nuclei with elliptical shapes. This descriptor classifies the nuclei regions based on two ellipticity parameters. Nuclei clumps and nuclei with irregular shapes are then localized by an improved seed detection technique based on voting in the eroded nuclei regions. Finally, undivided nuclei regions are segmented by a marked watershed algorithm. Experimental results on 114 different image patches indicate that the proposed technique provides a superior performance in nuclei detection and segmentation.
  • Keywords
    cellular biophysics; image segmentation; medical image processing; object detection; skin; adaptive threshold technique; cell nuclei segmentation; ellipse descriptor analysis; improved seed detection algorithm; marked watershed algorithm; nuclei clumps; skin histopathological images; Algorithm design and analysis; Clustering algorithms; Image segmentation; Informatics; Kernel; Shape; Skin; Ellipse descriptor; histopathological images; nuclei segmentation; seed detection; watershed algorithm;
  • fLanguage
    English
  • Journal_Title
    Biomedical and Health Informatics, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    2168-2194
  • Type

    jour

  • DOI
    10.1109/JBHI.2013.2297030
  • Filename
    6698355