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
Link To Document