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Title: Neural network approach for Compton-scattering imaging
Authors: Wang, J
Wang, Y
Chi, ZG 
Keywords: Algorithms
Computer simulation
Image processing
Neural networds (computer)
Issue Date: 1-Sep-1998
Publisher: Optical Society of America
Source: Journal of the Optical Society of America. A, Optics, image science, and vision, 1 Sept. 1998, v. 15, no. 9, p. 2297-2301 How to cite?
Journal: Journal of the Optical Society of America. A, Optics, image science, and vision 
Abstract: The problem of image reconstruction with Compton-scattering spectral data is an ill-posed problem, and the measurement error may be seriously amplified in the reconstruction result. For a stable solution, some kinds of a priori models of the problem should be incorporated into the process of reconstruction. Lee et al. [IEEE. Trans. Nucl. Sci. 40, 2049 (1993)] have proposed a continuous model with binary line processes. Owing to the coexistence of the continuous variable and the binary variable, the commonly used optimization methods for problems with continuous variables cannot be used in this case, and therefore a coupled-gradient artificial neural network was proposed for this mixed-integer problem. By introducing two interacting parts (with one part for the continuous variable and the other for the binary line processes) into the network, and by defining the appropriate energy function and dynamics, high-quality solutions were obtained upon convergence of the dynamics. Some simulated results are presented.
ISSN: 1084-7529
EISSN: 1520-8532
DOI: 10.1364/JOSAA.15.002297
Rights: © 1998 Optical Society of America. This paper was published in Journal of the Optical Society of America A and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
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