• DocumentCode
    1145120
  • Title

    Delineating Elliptical Objects with an Application to Cardiac Scintigrams

  • Author

    Blokland, Jacobus A.K. ; Vossepoel, Albert M. ; Bakker, Albert R. ; Pauwels, Ernest K.J.

  • Volume
    6
  • Issue
    1
  • fYear
    1987
  • fDate
    3/1/1987 12:00:00 AM
  • Firstpage
    57
  • Lastpage
    66
  • Abstract
    To delineate the myocardium in planar thallium-201 scintigrams of the left ventricle, a method, based on the Hough transformation, is presented. The method maps feature points (X, Y, Y´)-where Y´ reflects the direction of the tangent in edge point (X,Y)-into the two-dimensional space of the axis lengths of the ellipse. Within this space, a probability density function (pdf) can be estimated. When the center of the ellipse or its orientation are unknown, the 2-D pdf of the lengths of the axes is extended to a 5-D pdf of all parameters of the ellipse (lengths of the axes, coordinates of the center, and the orientation). It is shown that the variance of the edge-point-based estimates of the axis lengths increases when the location error of the center of the supposed ellipse or its orientation error increases. The likelihood of the estimates is expected to decrease with increasing variance. Therefore, local search algorithms can be applied to find the maximum likelihood estimate of the parameters of the ellipse. Curves describing the convergency of the algorithm are presented, as well as an example of the application of the algorithm to real scintigrams. The method is able to detect contours even if they are only partly visualized, as in thallium scintigrams of the myocardium of patients with ischemic heart disease. As long as the number of parameters describing the contour is relatively low, such an algorithm is also suitable for application to differently curved contours.
  • Keywords
    Cameras; Jacobian matrices; Lesions; Maximum likelihood detection; Maximum likelihood estimation; Myocardium; Parameter estimation; Pixel; Probability density function; Signal to noise ratio;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.1987.4307798
  • Filename
    4307798