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New genetic operators in the fly algorithm: application to medical PET image reconstruction

Abstract : Our reconstruction method is based on a cooperative coevolution strategy (also called Parisian evolution): the "fly algorithm". Each fly is a 3D point that mimics a positron emitter. The flies' position is progressively optimised using evolutionary computing to closely match the data measured by the imaging system. The performance of each fly is assessed using a "marginal evaluation" based on the positive or negative contribution of this fly to the performance of the population. Using this property, we propose a "thresholded-selection" method to replace the classical tournament method. A mitosis operator is also proposed. It is triggered to automatically increase the population size when the number of flies with negative fitness becomes too low.
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Submitted on : Friday, February 1, 2013 - 5:27:05 PM
Last modification on : Tuesday, October 25, 2022 - 4:16:48 PM
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  • HAL Id : hal-00783832, version 1


Franck P. Vidal, Jean Louchet, Jean-Marie Rocchisani, Evelyne Lutton. New genetic operators in the fly algorithm: application to medical PET image reconstruction. EVOIASP, Evolutionary Computation in Image Analysis and Signal Processing, EvoApplications 2010, Apr 2010, Istambul, Turkey. ⟨hal-00783832⟩



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