• DocumentCode
    1831232
  • Title

    Reduced Speckle noise on Medical Ultrasound Images Using Cellular Neural Network

  • Author

    Hyunkyung Park ; Nishimura, T.

  • Author_Institution
    Waseda Univ., Tokyo
  • fYear
    2007
  • fDate
    22-26 Aug. 2007
  • Firstpage
    2138
  • Lastpage
    2141
  • Abstract
    Speckle noise is indispensable get from ultrasound image. In general tends to reduce the image resolution and contrast. In addition to the doctor diagnosis, is lacking for judgment accuracy. This paper is reduced the speckle noise and enhanced boundary of a tumor in the medical ultrasound images. The proposed method is valuated using numerical phantom simulating ultrasound B-mode images, and the effect is confirmed by applying to medical ultrasound images. Therefore, some important features such as tissue boundaries and small tumors may be overlooked. A cellular neural network which is a kind of recurrent neural network can deal with images by the weight of neurons called a cell. It could be obtained more detail images recognition compared with the previous studies. Determination template parameters of the cellular neural network for ultrasound image processing are discussed. The experimental results show effectiveness of applying the proposed method to boundary enhancement and the speckle noise reduction of medical ultrasound image.
  • Keywords
    biomedical ultrasonics; image denoising; image recognition; image resolution; medical image processing; phantoms; recurrent neural nets; tumours; cellular neural network; image contrast; image recognition; image resolution; medical ultrasound images; phantom; recurrent neural network; reduced speckle noise; tumor; ultrasound B-mode images; Biomedical imaging; Cellular neural networks; Image resolution; Imaging phantoms; Medical diagnostic imaging; Neoplasms; Noise reduction; Numerical simulation; Speckle; Ultrasonic imaging; Algorithms; Artifacts; Equipment Design; Humans; Image Interpretation, Computer-Assisted; Image Processing, Computer-Assisted; Models, Statistical; Neoplasms; Nerve Net; Neural Networks (Computer); Neurons; Signal Processing, Computer-Assisted; Subtraction Technique; Ultrasonics; Ultrasonography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
  • Conference_Location
    Lyon
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-0787-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2007.4352745
  • Filename
    4352745