• DocumentCode
    510311
  • Title

    Soft-Threshold De-noising Method of Medical Ultrasonic Image Based on PCNN

  • Author

    Ye-Cai Guo ; Long-qing He ; Shao-Bo Wang

  • Author_Institution
    Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • Volume
    3
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    554
  • Lastpage
    558
  • Abstract
    Based on the analysis of the speckle noise´s properties, a soft-threshold de-noising method of medical ultrasonic image based on PCNN was proposed. In the proposed method, wavelet transform can produce the coefficients which contain the distinct characteristics of input information and make coarse-to-fine multi-resolution analysis for signal, and PCNN can recognize signals, it is realized that PCNN recognizes the coefficients of high frequency in wavelet domain, and then the wavelet coefficients are processed by corresponding methods, the speckle noises can be removed. The experimental results show that the Peak Signal to Noise Ratio (PSNR) is higher and the details of images are kept as more as possible, meanwhile, the edge blur phenomenon caused by wavelet threshold de-noising is improved.
  • Keywords
    image denoising; medical image processing; neural nets; coarse-to-fine multiresolution analysis; medical ultrasonic image; peak signal to noise ratio; pulse coupled neural networks; soft-threshold denoising method; wavelet transform; Biomedical imaging; Character recognition; Image analysis; Noise reduction; PSNR; Signal processing; Speckle; Wavelet analysis; Wavelet domain; Wavelet transforms; PCNN; PSNR; speckle noises; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.372
  • Filename
    5376814