13 October 1997 Evolutionary approach to image reconstruction from projections
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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.
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Zensho Nakao, Fathelalem Fadlallah Ali, Midori Takashibu, Yen-Wei Chen, "Evolutionary approach to image reconstruction from projections", Proc. SPIE 3165, Applications of Soft Computing, (13 October 1997); doi: 10.1117/12.279588; https://doi.org/10.1117/12.279588
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