• DocumentCode
    3280457
  • Title

    Based on pre-treatment and region growing segmentation method of liver

  • Author

    Yan, Zhennan ; Wang, Wenhan ; Yu, Hexin ; Huang, Jin

  • Author_Institution
    Software Coll., Northeast Univ., Liaoning, China
  • Volume
    3
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    1338
  • Lastpage
    1341
  • Abstract
    As the traditional image segmentation methods cannot show the located targets of object clearly and accurately. The paper is based on pre-treatment and 3D region growing segmentation method of the liver. First of all, the original abdominal volume data is based on improving image edges and thresholding segmentation algorithm which is based on statistical analysis to achieve pre-treatment; Secondly, the volume data after pre-treatment is based on volume rendering which is based on RC algorithm to achieve three-dimensional visualization of abdominal CT images; Then, based on 3D region growing algorithm for three-dimensional abdominal images of liver segmentation. Through the design of the liver segmentation experiment from abdominal CT images to validate the effectiveness of the method of the paper.
  • Keywords
    computerised tomography; data visualisation; image segmentation; liver; medical image processing; rendering (computer graphics); statistical analysis; 3D region growing segmentation; 3D visualization; RC algorithm; abdominal CT images; image edges; image segmentation; liver; original abdominal volume data; pre-treatment; statistical analysis; thresholding segmentation algorithm; volume rendering; Algorithm design and analysis; Image color analysis; Image edge detection; Image segmentation; Liver; Mathematical model; Three dimensional displays; Statistical analysis; improving image edges; region growing algorithm; threshold segmentation algorithm; volume data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2010 3rd International Congress on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6513-2
  • Type

    conf

  • DOI
    10.1109/CISP.2010.5648010
  • Filename
    5648010