• DocumentCode
    3622236
  • Title

    Interpretation of Uroflow Graphs with Artificial Neural Networks

  • Author

    Altunay; Telatar; Erogul; Aydur

  • Author_Institution
    EAS Elektronik Sanayi Ticaret A.Ş
  • fYear
    2006
  • fDate
    6/28/1905 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Uroflowmetry is a measuring method, which provides numerical and graphical information about patient´s lower urinary tract dynamics by measuring and plotting the rate of change of voided urine volume. The main purpose of the study is to evaluate uroflowmetric data using artificial neural networks (ANN) and provide a pre-diagnostic result for urology specialists. The ANN is trained using back-propagation method and the inputs of ANN are the results of a special feature extraction algorithm, which is designed with the suggestions of urology specialists. System´s success is monitored with a set of data, which was already diagnosed by specialists. The outputs of ANN are classified into three groups, namely, "healthy", "possible pathologic" and "pathologic"
  • Keywords
    "Artificial neural networks","Volume measurement","Testing","Argon","Feature extraction","Algorithm design and analysis","Monitoring","Abdomen","Medical diagnostic imaging"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications, 2006 IEEE 14th
  • ISSN
    2165-0608
  • Print_ISBN
    1-4244-0238-7
  • Type

    conf

  • DOI
    10.1109/SIU.2006.1659698
  • Filename
    1659698