Share Email Print

Proceedings Paper

Evolutionary approach to image reconstruction from projections
Author(s): Zensho Nakao; Fathelalem Fadlallah Ali; Midori Takashibu; Yen-Wei Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We present an evolutionary approach for reconstructing CT images; the algorithm reconstructs two-dimensional unknown images from four one-dimensional projections. A genetic algorithm works on a randomly generated population of strings each of which contains encodings of an image. The traditional, as well as new, genetic operators are applied on each generation. The mean square error between the projection data of the image encoded into a string and original projection data is used to estimate the string fitness. A Laplacian constraint term is included in the fitness function of the genetic algorithm for handling smooth images. Two new modified versions of the original genetic algorithm are presented. Results obtained by the original algorithm and the modified versions 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 in the particular case of limiting projection directions to four.

Paper Details

Date Published: 13 October 1997
PDF: 9 pages
Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.279588
Show Author Affiliations
Zensho Nakao, Univ. of the Ryukyus (Japan)
Fathelalem Fadlallah Ali, Univ. of the Ryukyus (Japan)
Midori Takashibu, Univ. of the Ryukyus (Japan)
Yen-Wei Chen, Univ. of the Ryukyus (Japan)

Published in SPIE Proceedings Vol. 3165:
Applications of Soft Computing
Bruno Bosacchi; James C. Bezdek; David B. Fogel, Editor(s)

© SPIE. Terms of Use
Back to Top