• DocumentCode
    958063
  • Title

    Fan-beam reconstruction methods

  • Author

    Horn, Berthold K P

  • Author_Institution
    M.I.T. Artificial Intelligence Laboratory, Cambridge, MA
  • Volume
    67
  • Issue
    12
  • fYear
    1979
  • Firstpage
    1616
  • Lastpage
    1623
  • Abstract
    In a previous paper a technique was developed for finding reconstruction algorithms for arbitrary ray-sampling schemes. The resulting algorithms use a general linear operator, the kernel of which depends on the details of the scanning geometry. Here this method is applied to the problem of reconstructing density distributions from arbitrary fan-beam data. The general fan-beam method is then specialized to a number of scanning geometries of practical importance. Included are two cases where the kernel of the general linear operator can be factored and rewritten as a function of the difference of coordinates only and the superposition integral consequently simplifies into a convolution integral. Algorithms for these special cases of the fan-beam problem have been developed previously by others. In the general case, however, Fourier transforms and convolutions do not apply, and linear space-variant operators must be used. As a demonstration, details of a fan-beam method for data obtained with uniform ray-sampling density are developed.
  • Keywords
    Artificial intelligence; Density measurement; Fourier transforms; Geometry; Integral equations; Jacobian matrices; Kernel; Paper technology; Reconstruction algorithms; Sampling methods;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/PROC.1979.11542
  • Filename
    1455811