References for Tomographic Image

Tomographic Image Reconstruction Algorithm Development

	Optical tomography using a genetic algorithm
	Adoption of a genetic algorithm (GA) for tomographic reconstruction of line-of-sight optical images
	Tomographic-image reconstruction using a hybrid genetic algorithm
	Tomographic identification of gas bubbles in two-phase flows with the combined use of the algebraic reconstruction technique and the genetic algorithm

Optical tomography using a genetic algorithm

Ken D. Kihm and Donald P. Lyons

A new tomographic image reconstruction method is proposed that uses a genetic algorithm (GA), a robust optimization algorithm based on the genetic principle of natural selection. For the purpose of description, a simple axisymmetric reference density field is reconstructed from its interferometric projection by the developed GA-based tomography. This preliminary investigation shows a promising potential of the GA-based tomography to overcome the problems associated with other existing tomographic methods, particularly for limited projections. ? 1996 Optical Society of America

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Adoption of a genetic algorithm (GA) for tomographic reconstruction of line-of-sight optical images

K. D. Kihm, K. Okamoto, D. Tsuru, H. S. Ko

A new tomographic reconstruction scheme is pro-posed that uses a genetic algorithm (GA), a robust and com-binatorial function optimization based on the mechanics of the genetic principle. The paper first discusses the implicitly parallel and scaled random nature of the GA optimization using an illustrative example. An introduction of the elementary distribution function (EDF) to constitute the cross-sectional
field shows a successful adoption of GA for optical tomography. The GA-based tomography was examined for interferometric projections of computer-synthesized phantom density fields. The GA-based tomography shows accurate and stable image reconstruction, particularly for limited projections.

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Tomographic-image reconstruction using a hybrid genetic algorithm

Donald P. Lyons and Ken D. Kihm

An improved tomographic-image reconstruction method is proposed that uses a hybrid genetic algorithm (GA) that hybridizes a conventional GA and a concurrent simplex method. For the purposes of discussion, an axisymmetric phantom density field is used with an interferometric optical projection. Tomographic-image reconstruction using the hybrid GA not only improves the convergence over the pure GA but also significantly reduces the computation time. ? 1997 Optical Society of America

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Tomographic identification of gas bubbles in two-phase flows
with the combined use of the algebraic reconstruction technique and the genetic algorithm

Ken D. Kihm, H. S. Ko, and Donald P. Lyons

Combined use of the algebraic reconstruction technique (ART) and the genetic algorithm (GA) shows highly accurate and efficient tomographic reconstruction of line-of-sight projection images of two-phase flows compared with reconstructions obtained by separate use of these methods. A modified GA-based tomography uses the ART reconstruction result as preliminary information on the number, shapes, and sizes of bubbles to be reconstructed. This combined use of the two methods exploits faster convergence of the ART to the approximate solution space and more robust and accurate optimization of the GA to the ultimate solution space. In the investigation a computer-synthesized phantom field that consisted of five elliptical gas bubbles in liquid or solid surroundings was used.

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