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Swarm Optimised Few-View Binary Tomography

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Applications of Evolutionary Computation (EvoApplications 2022)

Abstract

This paper considers a swarm optimisation approach to few-view tomographic reconstruction. DFOMAX, a high diversity swarm optimiser, demonstrably reconstructs binary images to a high fidelity, outperforming a leading algebraic technique, differential evolution and particle swarm optimisation on four standard phantoms. The paper considers the effectiveness of optimisers that have been developed for optimal low dimensional performance and concludes that trial solution clamping on the walls of the feasible search space is important for good performance.

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Acknowledgement

The authors would like to thank Darren Wise for his support in facilitating access to the HPC machines at the University of Greenwich.

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Correspondence to Mohammad Majid al-Rifaie .

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al-Rifaie, M.M., Blackwell, T. (2022). Swarm Optimised Few-View Binary Tomography. In: Jiménez Laredo, J.L., Hidalgo, J.I., Babaagba, K.O. (eds) Applications of Evolutionary Computation. EvoApplications 2022. Lecture Notes in Computer Science, vol 13224. Springer, Cham. https://doi.org/10.1007/978-3-031-02462-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-02462-7_3

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