• DocumentCode
    1692566
  • Title

    Automatic Diagnosis of Liver Diseases from Ultrasound Images

  • Author

    Zaid, Abou Zaid Sayed Abou ; Fakhr, Mohamed Waleed ; Mohamed, Ahmed Farag Ali

  • fYear
    2006
  • Firstpage
    313
  • Lastpage
    319
  • Abstract
    Ultrasound is a widely used medical imaging technique. Tissue characterization with ultrasound has become important topic since computer facilities have been available for the analysis of ultrasound signals. Automatic liver tissue characterizations from ultrasonic scans have been long the concern of many researchers. Different techniques has been used ranging from processing the RF signals received by the transducer to using neural networks to analyze images based on image texture. In this paper, an automatic liver diseases diagnostic system is implemented for early detection of liver diseases. The proposed system classification accuracy is 96.125%. The system advantage is its high accuracy and its computation simplicity. The system can be used as a second opinion system to aid the diagnosis of liver diseases
  • Keywords
    biomedical ultrasonics; cancer; image texture; liver; medical image processing; neural nets; tumours; ultrasonic transducers; RF signals processing; automatic diagnosis; image analysis; image texture; liver cancer; liver diseases; medical imaging technique; neural networks; tissue characterization; ultrasonic scans; ultrasound images; ultrasound signal analysis; ultrasound transducer; Brightness; Cancer; Data mining; Elasticity; Image texture; Liver diseases; Neural networks; Pathology; Signal analysis; Ultrasonic imaging; Ultrasound imaging; automatic liver diagnoses; neural networks; quantitative tissue characterization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Systems, The 2006 International Conference on
  • Conference_Location
    Cairo
  • Print_ISBN
    1-4244-0271-9
  • Electronic_ISBN
    1-4244-0272-7
  • Type

    conf

  • DOI
    10.1109/ICCES.2006.320467
  • Filename
    4115527