• DocumentCode
    1588026
  • Title

    Cellular Neural Network Based Urinary Image Segmentation

  • Author

    Zhang, Zanchao ; Xia, Shunren ; Duan, Huilong

  • Author_Institution
    Zhejiang Univ., Hangzhou
  • Volume
    2
  • fYear
    2007
  • Firstpage
    285
  • Lastpage
    289
  • Abstract
    A novel approach for urinary image segmentation based on cellular neural network (CNN) was presented in this paper. Before the image segmentation, a preprocessing by stretching the difference between every pixel and the local gray mean value for eliminating the disequilibrium of illumination and enhancing the edges of objects is considered here. The experiment results with more than 100 clinical urinary images show that this approach provides more accurate objects detection compared with conventional threshold based ones.
  • Keywords
    cellular neural nets; image segmentation; medical image processing; object detection; cellular neural network; illumination disequilibrium; local gray mean value; objects detection; urinary image segmentation; Cellular neural networks; Diseases; Histograms; Image edge detection; Image segmentation; Lighting; Microscopy; Morphology; Pixel; Sediments; Urinary microscopic image; cellular neural network (CNN); distance transform; grayaverage-; object enhancement; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2007. ICNC 2007. Third International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2875-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2007.294
  • Filename
    4344361