• DocumentCode
    1991761
  • Title

    Tissue Identification in Ultrasound Images using Rayleigh Local Parameter Estimation

  • Author

    Aja-Fernandez, Santiago ; Martin-Fernandez, Marcos ; Alberola-López, Carlos

  • Author_Institution
    Univ. de Valladolid, Valladolid
  • fYear
    2007
  • fDate
    14-17 Oct. 2007
  • Firstpage
    1129
  • Lastpage
    1133
  • Abstract
    A method to identify different tissues in ultrasound images is presented. Assuming a Rayleigh model for speckle, the different tissues present in the image will be related to the Rayleigh sigma parameter, with different values for each different tissue. The parameter is locally estimated using well known estimation methods for the Rayleigh distribution, such as the maximum likelihood estimator. A significant increase in the separability of the different tissues present in the image is then achieved. A subsequent clustering process based on the position of the maxima of the estimator distribution allows the classification of each pixel in a tissue class.
  • Keywords
    biological tissues; biomedical ultrasonics; maximum likelihood estimation; medical image processing; speckle; Rayleigh distribution; Rayleigh local parameter estimation; clustering; maximum likelihood estimator; speckle; tissues; ultrasound images; Dynamic range; Image coding; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Radar scattering; Rayleigh scattering; Speckle; Telecommunication standards; Ultrasonic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Bioengineering, 2007. BIBE 2007. Proceedings of the 7th IEEE International Conference on
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-1509-0
  • Type

    conf

  • DOI
    10.1109/BIBE.2007.4375702
  • Filename
    4375702