• DocumentCode
    3083141
  • Title

    Generalized Caseview applied to prostate cancer prognosis

  • Author

    Levy, Pierre P. ; Bardier, Armelle ; Doublet, Jean-Dominique ; Sibony, Mathilde

  • Author_Institution
    Public Health Department Hÿpital Tenon, Assistance Publique Hÿpitaux de Paris, 4 rue de la Chine, 75970, Cedex 20, France
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    5129
  • Lastpage
    5131
  • Abstract
    The interpretation of results of any study using large tables with series of numbers is always difficult. Generalized Case View Method (GCm) allows translating these tables of numbers into an image. The Method identifies each informational entity in the table with a “pixel”, forming what we call an “infoxel”. The sum of all informational entities becomes an image, the Generalized Caseview. The method consists of two steps: the first one is to define the reference frame while the second is to visualize data through the reference frame. The “infoxels” that constitute the reference frame should be organized according to three criteria: binary, nominal and ordinal. Here this method has been applied to visualize the results of a study about prostate cancer spread. This paper exemplifies the usefulness of associating a classical statistical tool with Generalized Caseview method to solve a biomedical problem.
  • Keywords
    Anatomy; Biomedical imaging; Biopsy; Data visualization; Histograms; Pathology; Prostate cancer; Public healthcare; Statistical analysis; Tumors; Artificial Intelligence; Biopsy; Computer Graphics; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Humans; Male; Pattern Recognition, Automated; Prostatic Neoplasms; Reproducibility of Results; Sensitivity and Specificity; User-Computer Interface;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4650368
  • Filename
    4650368