Swarm Led Tomographic Reconstruction

al-Rifaie, Mohammad Majid and Blackwell, Tim. 2022. 'Swarm Led Tomographic Reconstruction'. In: Genetic and Evolutionary Computation Conference (GECCO ’22). Boston, MA, United States 9 - 13 July 2022. [Conference or Workshop Item]

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Abstract or Description

Image reconstruction from ray projections is a common technique in medical imaging. In particular, the few-view scenario, in which the number of projections is very limited, is important for cases where the patient is vulnerable to potentially damaging radiation. This paper considers swarm-based reconstruction where individuals, or particles, swarm in image space in an attempt to lower the reconstruction error. We compare several swarm algorithms with standard algebraic reconstruction techniques and filtered back-projection for five standard test phantoms viewed under reduced projections. We find that although swarm algorithms do not produce solutions with lower reconstruction errors, they generally find more accurate reconstructions; that is, swarm techniques furnish reconstructions that are more similar to the original phantom. A function profiling method suggests that the ability of the swarm to optimise these high dimensional problems can be attributed to a broad funnel leading to complex structure close to the optima. This finding is further exploited by optimising the parameters of the best performing swarm technique, and the results are compared against three unconstrained and boxed local search methods. The tomographic reconstruction-optimised swarm technique is shown to be superior to prominent algebraic reconstructions and local search algorithms.

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Conference or Workshop Item (Paper)

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"© 2022 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record is available at, https://doi.org/10.1145/3512290.3528737."


swarm optimisation, function profiling, tomographic reconstruction

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8 July 2022Published

Event Location:

Boston, MA, United States

Date range:

9 - 13 July 2022

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Date Deposited:

27 Sep 2023 12:44

Last Modified:

12 Oct 2023 20:27



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