Genetic connectionism for computed tomographic reconstructions

Salah Darenfed

doi:10.1117/12.148712

29 July 1993 Genetic connectionism for computed tomographic reconstructions

Salah Darenfed

Author Affiliations +

Proceedings Volume 1905, Biomedical Image Processing and Biomedical Visualization; (1993) https://doi.org/10.1117/12.148712
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

The reconstruction of a transparent medium from projections acquired from a limited angle of view of formulated as a combinatorial optimization problem. Given a description of a phantom object, the necessary optical pathlength data are computed by numerical quadrature for a small angle of view. The objective is to distribute these object units among all object cells, such that the resulting distribution is the most probable one consistent with the projection data. The reconstruction problem is based on a network comprised of 3 layers. A Genetic based algorithm (GAs) finds the adjustable network coefficients which represent the 2D Fourier components. The object units are coded as a population of strings. New strings are generated through the use of genetic operators: probabilistic selection (reproduction), crossover (recombination of parental solutions) and mutation (exploration in the neighborhood of the current solution). Unlike iterative improvement which proceeds from one point, GAs use a population-by-population search procedures resulting in global search procedure. A hypothetical object field in the form of a mathematical phantom is reconstructed.

Citation Download Citation

Salah Darenfed "Genetic connectionism for computed tomographic reconstructions", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); https://doi.org/10.1117/12.148712

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