• DocumentCode
    314354
  • Title

    Evolutionary CT image reconstruction

  • Author

    Nakao, Zensho ; Takashibu, Midori ; Ali, Fath El Alem F ; Chen, Yen-wei

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa, Japan
  • Volume
    3
  • fYear
    1997
  • fDate
    9-12 Jun 1997
  • Firstpage
    1608
  • Abstract
    An evolutionary algorithm for reconstructing CT gray images from projections is presented; the algorithm reconstructs two-dimensional unknown images from four one-dimensional projections. A Laplacian constraint term is included in the fitness function of the genetic algorithm for handling smooth images, and the evolutionary process reconstructs images into finer ones by partitioning the images gradually thereby increasing the chromosome size exponentially as the generation proceeds. Results obtained are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the evolutionary method is more effective than ART when the number of projection directions is very limited
  • Keywords
    computerised tomography; genetic algorithms; image reconstruction; medical image processing; 1D projections; 2D unknown images; Laplacian constraint term; chromosome size; evolutionary CT image reconstruction; fitness function; genetic algorithm; gray images; image partitioning; smooth images; Biological cells; Computed tomography; Electronic mail; Evolutionary computation; Genetic algorithms; Image reconstruction; Laplace equations; Partitioning algorithms; Pixel; Subspace constraints;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks,1997., International Conference on
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-7803-4122-8
  • Type

    conf

  • DOI
    10.1109/ICNN.1997.614134
  • Filename
    614134