• DocumentCode
    3010805
  • Title

    An intelligent system for renal segmentation

  • Author

    Aribi, Yassine ; Wali, Ali ; Alimi, Adel M.

  • Author_Institution
    REGIM: Res. Groups on Intell. Machines, Univ. of Sfax, Sfax, Tunisia
  • fYear
    2013
  • fDate
    9-12 Oct. 2013
  • Firstpage
    11
  • Lastpage
    15
  • Abstract
    Scintigraphic images are often characterized with much noise and a badly contrasted resolution which makes the perception of regions of interest very difficult. The renal quantification is how to define the regions of interests whose activities informs on the status of the renal function. In this context, the current study presents an intelligent system for the segmentation of renal regions in order to facilitate the process of quantification. The use of a multi-agent system based on the HOG3D descriptor combined with Fast Marching Method, has made our System of segmentation faster and more accurate. This automatic segmentation system is expected to assist physicians in both clinical diagnosis and educational training. Experiments and tests were developed on a database including 1800 images from 15 patients selected to obtain a variety of images. The results of the application of our method on several dynamic images are presented and discussed.
  • Keywords
    image segmentation; knowledge based systems; medical image processing; patient diagnosis; radioisotope imaging; HOG3D descriptor; automatic segmentation system; clinical diagnosis; educational training; fast marching method; intelligent system; multiagent system; renal function; renal quantification; renal regions; renal segmentation; scintigraphic images; Algorithm design and analysis; Conferences; Educational institutions; Image segmentation; Kidney; Manuals; Multi-agent systems; Fast Marching Method; Hog3D; Multi-Agent System; Renal Quantification; Scintigraphics images; intelligent system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Health Networking, Applications & Services (Healthcom), 2013 IEEE 15th International Conference on
  • Conference_Location
    Lisbon
  • Print_ISBN
    978-1-4673-5800-2
  • Type

    conf

  • DOI
    10.1109/HealthCom.2013.6720629
  • Filename
    6720629