• DocumentCode
    3300420
  • Title

    Microscopic Image Segmentation for the Clinical Support System

  • Author

    Ko, ByoungChul ; Seo, MiSuk ; Nam, JaeYeal

  • Author_Institution
    Dept. of Comput. Eng., Keimyung Univ., Daegu
  • fYear
    2007
  • fDate
    14-17 Aug. 2007
  • Firstpage
    489
  • Lastpage
    494
  • Abstract
    This paper presents an AAW (adaptive attention window)-based microscopic cell image segmentation method. For semantic AAW detection, a luminance map is used to create an initial attention window, which is then reduced close to the size of the real ROI (region of interest) using a quad-tree. The purpose of the AAW is to facilitate background removal and reduce the ROI segmentation processing time. Region segmentation is performed within the AAW, followed by region clustering and removal to produce segmentation of only ROIs. Experimental results demonstrate that the proposed method can efficiently segment one or more ROIs and produce similar segmentation results to human perception.
  • Keywords
    image segmentation; medical image processing; pattern clustering; quadtrees; adaptive attention window; clinical support system; luminance map; microscopic cell image segmentation method; quad-tree; region clustering; region of interest; region segmentation; Biomedical imaging; Cancer; Genomics; Humans; Image analysis; Image retrieval; Image segmentation; Lesions; Medical diagnostic imaging; Microscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Graphics, Imaging and Visualisation, 2007. CGIV '07
  • Conference_Location
    Bangkok
  • Print_ISBN
    0-7695-2928-3
  • Type

    conf

  • DOI
    10.1109/CGIV.2007.58
  • Filename
    4293718